Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Colorism on Historically Black Fraternities and Sororities

This dissertation study was conducted in order to examine and gain an insight on two topics that are considered to be highly under researched: American historically black fraternities and sororities and colorism within the back American community. The purpose of the study was to examine the impact that colorism has had on black American collegiate Greek letter organizations. Using the qualitative phenomenological approach, 18 graduate or alumni members, two from each of the nine historically black Greek letter organizations that make up the National Pan-Hellanic Council were interviewed using open ended questions to see what impact (if any) colorism has had on historically black fraternities and sororities. During the interviews the following five major themes emerged: discriminatory practices between black Americans, stereotyping black Greek letter organizations, stereotyping skin tones, colorism as a part of American history, and colorism as being permanently a part of the black American community. The following theories were also explored during the study: Social Identity Theory, Double Consciousness, Primary Identification Theory, and Conflict Caused by Colorism, to further see what impact colorism had on historically black fraternities and sororities. Through these five themes and theories, it was found that colorism has had and continues to have a significant impact on not only members of historically black fraternities and sororities, but also that of members of the black American community as a whole.
Alpha-Mangostin Attenuation of Hyperglycemia-Induced Ocular Hypoperfusion and Blood Retinal Barrier Leakage in the Early Stage of Type 2 Diabetes Rats

The present study examined effects of alpha-mangostin (α-MG) supplementation on the retinal microvasculature, including ocular blood flow (OBF) and blood-retinal barrier (BRB) permeability in a type 2 diabetic animal model. Male Sprague-Dawley rats were divided into four groups: normal control and diabetes with or without α-MG supplementation. Alpha-mangostin (200 mg/Kg/day) was administered by gavage feeding for 8 weeks. The effects of α-MG on biochemical and physiological parameters including mean arterial pressure (MAP), OBF, and BRB leakage were investigated. Additionally, levels of retinal malondialdehyde (MDA), advance glycation end products (AGEs), receptor of advance glycation end products (RAGE), tumour necrosis factor alpha (TNF-α), and vascular endothelial growth factor (VEGF) were evaluated. The elevated blood glucose, HbA1c, cholesterol, triglyceride, serum insulin, and HOMA-IR were observed in DM2 rats. Moreover, DM2 rats had significantly decreased OBF but statistically increased MAP and leakage of the BRB. The α-MG-treated DM2 rats showed significantly lower levels of retinal MDA, AGEs, RAGE, TNF-α, and VEGF than the untreated group. Interestingly, α-MG supplementation significantly increased OBF while it decreased MAP and leakage of BRB. In conclusion, α-MG supplementation could restore OBF and improve the BRB integrity, indicating its properties closely associated with antihyperglycemic, antioxidant, anti-inflammatory, and antiglycation activities.
A middlebox control plane framework for wireless and mobile ip networks

In wireless and mobile IP networks there is a need to support a set of functions that are related to wireless QoS provisioning, resource optimizations, mobility and security management and operator policy enforcement. These requirements have lead to the frequent usage of so called middleboxes including header/payload compressors, performance enhancement proxies, tunnel endpoints, packet filters and redirectors, QoS schedulers and others. Unfortunately, the increasing usage of these types of devices often leads to undesirable artifacts called feature interactions. In this paper we propose a framework that aims to coordinate the operation of middleboxes such that feature interactions are avoided. The three main ideas are (1) the separation of the control plane from the distributed network nodes, (2) the usage of a middlebox function independent horizontal protocol that allows mobile hosts to communicate their desired service requests to the network and (3) the usage of a vertical protocol between the network control and user planes. We present two examples in which this framework helps eliminate the risk for feature interactions. We comment on the relationship between the end-to-end principle and this framework. Finally, we discuss how future middleboxes can fit into this framework.
Integrative Approach to Quality Assessment of Medical Journals Using Impact Factor, Eigenfactor, and Article Influence Scores

Background Impact factor (IF) is a commonly used surrogate for assessing the scientific quality of journals and articles. There is growing discontent in the medical community with the use of this quality assessment tool because of its many inherent limitations. To help address such concerns, Eigenfactor (ES) and Article Influence scores (AIS) have been devised to assess scientific impact of journals. The principal aim was to compare the temporal trends in IF, ES, and AIS on the rank order of leading medical journals over time. Methods The 2001 to 2008 IF, ES, AIS, and number of citable items (CI) of 35 leading medical journals were collected from the Institute of Scientific Information (ISI) and the http://www.eigenfactor. org databases. The journals were ranked based on the published 2008 ES, AIS, and IF scores. Temporal score trends and variations were analyzed. Results In general, the AIS and IF values provided similar rank orders. Using ES values resulted in large changes in the rank orders with higher ranking being assigned to journals that publish a large volume of articles. Since 2001, the IF and AIS of most journals increased significantly; however the ES increased in only 51% of the journals in the analysis. Conversely, 26% of journals experienced a downward trend in their ES, while the rest experienced no significant changes (23%). This discordance between temporal trends in IF and ES was largely driven by temporal changes in the number of CI published by the journals. Conclusion The rank order of medical journals changes depending on whether IF, AIS or ES is used. All of these metrics are sensitive to the number of citable items published by journals. Consumers should thus consider all of these metrics rather than just IF alone in assessing the influence and importance of medical journals in their respective disciplines.
Been There, Done That: What Your Mobility Traces Reveal about Your Behavior

Mobility is a central aspect of our life; the locations we visit reflect our tastes and lifestyle and shape our social relationships. The ability to foresee the places a user will visit is therefore beneficial to numerous applications, ranging from forecasting the dynamics of crowds to improving the relevance of location-based recommendations. To solve the Next Place Prediction task of the Nokia Mobile Data Challenge, we developed several mobility predictors, based on graphical models, neural networks, and decision trees, and explain some of the challenges that we faced. Then, we combine these predictors using different blending strategies, which improve the prediction accuracy over any individual predictor.
Network Measurements of a Wireless Classroom Network

The advent of mobile computers and wireless networks enables the deployment of wireless Web servers and clients in short-lived ad hoc network environments, such as classroom area networks. This paper studies wireless Web performance in a classroom environment. Experiments are conducted on an ad hoc IEEE 802.11b wireless LAN, using a wireless-enabled Apache Web server, several wireless clients, and a wireless network analyzer. The experiments focus on the HTTP performance and network throughput achievable in the wireless classroom environment.
Portfolio Optimization for Influence Spread

Motivated by viral marketing, stochastic diffusion processes that model influence spread on a network have been studied intensively. The primary interest in such models has been to find a seed set of a fixed size that maximizes the expected size of the cascade from it. Practically, however, it is not desirable to have the risk of ending with a small cascade, even if the expected size of the cascade is large. To address this issue, we adopt conditional value at risk (CVaR) as a risk measure, and propose an algorithm that computes a portfolio over seed sets with a provable guarantee on its CVaR. Using real-world social networks, we demonstrate that the portfolio computed by our algorithm has a significantly better CVaR than seed sets computed by other baseline methods.
A Learning Framework for Automatic Assume-Guarantee Verification

Compositional verification is a promising approach to addressing the state explosion problem associated with model checking. One compositional technique advocates proving properties of a system by checking properties of its components in an assume-guarantee style. However, the application of this technique is difficult because it involves non-trivial human input. This paper presents a novel framework for performing assume-guarantee reasoning in an incremental and fully automated fashion. To check a component against a property, our approach generates assumptions that the environment needs to satisfy for the property to hold. These assumptions are then discharged on the rest of the system. Assumptions are computed by a learning This paper is an extended and revised version of [10]. algorithm. They are initially approximate, but become gradually more precise by means of counterexamples obtained by model checking the component and its environment, alternately. This iterative process may at any stage conclude that the property is either true or false in the system. We have implemented our approach in the LTSA tool and discuss its application to a NASA system.
Recency, Repetition, and the Multidimensional Basis of Recognition Memory

Recency and repetition are two factors that have large effects on human memory performance. One way of viewing the beneficial impact of these variables on recognition memory is to assume that both factors modulate a unidimensional memory trace strength. Although previous functional neuroimaging studies have indicated that recency and repetition may modulate similar brain structures, particularly in the region of the inferior parietal cortex, there is extensive behavioral evidence that human subjects can make independent and accurate recognition memory judgments about both an item's recency and its frequency. In the present study, we used fMRI to examine patterns of brain activity during recognition memory for auditory–verbal stimuli that were parametrically and orthogonally manipulated in terms of recency and number of repetitions. We found in a continuous recognition paradigm that the lateral inferior parietal cortex, a region that has previously been associated with recollective forms of memory, is highly sensitive to recency but not repetition. In a multivariate analysis of whole-brain activation patterns, we found orthogonal components that dissociated recency and repetition variables, indicating largely independent neural bases underlying these two factors. The results demonstrate that although both recency and repetition dramatically improve recognition memory performance, the neural bases for this improvement are dissociable, and thus are difficult to explain in terms of access to a unitary memory trace.
Visual front-endwars: Viola-Jones face detector vs Fourier Lucas-Kanade

The performance of visual speech recognition (VSR) systems are significantly influenced by the accuracy of the visual front-end. The current state-of-the-art VSR systems use off-the-shelf face detectors such as Viola- Jones (VJ) which has limited reliability for changes in illumination and head poses. For a VSR system to perform well under these conditions, an accurate visual front end is required. This is an important problem to be solved in many practical implementations of audio visual speech recognition systems, for example in automotive environments for an efficient human-vehicle computer interface. In this paper, we re-examine the current state-of-the-art VSR by comparing off-the-shelf face detectors with the recently developed Fourier Lucas-Kanade (FLK) image alignment technique. A variety of image alignment and visual speech recognition experiments are performed on a clean dataset as well as with a challenging automotive audio-visual speech dataset. Our results indicate that the FLK image alignment technique can significantly outperform off-the shelf face detectors, but requires frequent fine-tuning.
Political Regimes and Economic Growth in Latin America

Living in a democratic society has been internationally recognized as a basic human right. While most of the literature tries to identify the effect of democracy on economic prosperity, little work has been done to understand the determinants of economic growth under democracy. This paper examines whether the determinants of economic growth in Latin America are sensitive to political institutions. We find two stark differences between democratic and autocratic growth: (1) democratic government consumption is significantly positive for economic growth. The opposite is true for autocratic government consumption. (2) The impact of human capital is only significant under democracies.
A Tree-Structured Classification Model Based on Label Semantic

Label Semantics is a random set based framework for Computing with Words. Imprecise concepts are modeled by the degrees of appropriateness of a linguistic expression as defined by a fuzzy set. An approach to decision tree induction based on this framework is studied and its performance when applied to realworld datasets is compared with the C4.5 and other machine learning algorithms. A method of classification under linguistic constraints was proposed and studied with experiments.
Ability of a neuro-ophthalmologist to estimate retinal nerve fiber layer thickness

Background Qualitative description of the optic disc has clinical value, but optical coherence tomography (OCT) has provided the ability to quantify retinal nerve fiber layer (RNFL) thickness. Methods We asked three neuro-ophthalmologists of at least 20 years’ experience to estimate the average OCT RNFL thickness of 37 eyes based on fundus photos. Results The overall correlation coefficient for RNFL thickness estimation variance between two physicians and between physician and OCT was 0.53. The likelihood that the RNFL thickness estimation between physicians, or between physician and OCT, was within 10 μm of each other was 47%–62%. All physicians had disparities in RNFL thickness estimation greater than 30 μm. Conclusion This study provides information on the ability of an experienced neuro-ophthalmologist to estimate the RNFL thickness based on fundus photos.
A New Training Principle for Stacked Denoising Autoencoders

In this work, a new training principle is introduced for unsupervised learning that makes the learned representations more efficient and useful. Using partially corrupted inputs instead, the denoising Auto encoder can obtain more robust and representative pattern of inputs than the traditional learning methods. Besides, this denoising Auto encoder can be stacked to form a deep network. The whole framework of training stacked denoising Auto encoders, which involved several supervised training methods in the framework, is given for image classification. Comparative experiments have shown that the model can resist noise of training examples powerfully and achieve better accuracy of image classification on MNIST database.
Detecting of optimal Li-ion battery charging frequency by using AC impedance technique

This paper aims to explore the optimal Li-ion battery charging frequency by using AC impedance technique. The experiment proves that the optimal charging frequency is the point of the minimum AC impedance. In such a situation of the battery charged by the optimal charging frequency, the charging time and charging efficiency are improved above 30.68% and 30.6%.
Uncertainty-based Design Optimization of Shape Memory Alloy Microgripper using Combined Cycle-based Alternating Anti-optimization and Nested Parallel Computing

1. Abstract In this paper a cycle-based alternating anti-optimization approach using Bounded-But-Unknown uncertainties is studied on the basis of a practical application. The underlying optimization technique is based on use of Response Surface and undergoes series of cycles before it can converge. The basic anti-optimization technique looks at the worst case scenario by finding the worst settings of the uncertainties for each constraint evaluation separately. This Rigorous anti-optimization technique involves two-level optimization, in which anti-optimization is nested within the main optimization, making it computationally exhaustive. In order to make the anti-optimization technique computationally efficient, in the cycle-based alternating technique, anti-optimization is carried out at the end of every cycle of the main optimization instead of at every design during the cycle. Additionally, in the present paper, a nested parallel computing strategy is developed in order to make the cycle-based alternating technique computationally efficient when a cluster of computers is available for function evaluations in parallel. This is particularly essential in case of practical problems involving expensive function evaluations, such as using Finite Element Analysis. In this paper, the cycle-based alternating technique combined with nested parallel computing is applied to the uncertainty-based shape optimization of a Shape Memory Alloy Microgripper. 2.
Exploring the protein G helix free‐energy surface by solute tempering metadynamics

The free‐energy landscape of the α‐helix of protein G is studied by means of metadynamics coupled with a solute tempering algorithm. Metadynamics allows to overcome large energy barriers, whereas solute tempering improves the sampling with an affordable computational effort. From the sampled free‐energy surface we are able to reproduce a number of experimental observations, such as the fact that the lowest minimum corresponds to a globular conformation displaying some degree of β‐structure, that the helical state is metastable and involves only 65% of the chain. The calculations also show that the system populates consistently a π‐helix state and that the hydrophobic staple motif is present only in the free‐energy minimum associated with the helices, and contributes to their stabilization. The use of metadynamics coupled with solute tempering results then particularly suitable to provide the thermodynamics of a short peptide, and its computational efficiency is promising to deal with larger proteins. Proteins 2008. © 2007 Wiley‐Liss, Inc.
Visualizing City Events on Search Engine: Tword the Search Infrustration for Smart City

City big data play the central role in the whole smart city system architecture, where the search engine acts as the entrance to these big data. In this paper, we focus on the topic of events management in the city. By visualizing the search results beyond the traditional page-list manner, we can provide more valuable insight of the important events occurring in the city. Our development comprises three aspects: (i) the elementary representations of one city event. Here, two manners are proposed: one for the emergency event real time detecting & tracing, the other continuously aggregating the data to describe the event completely, (ii) the high order city event(s) representations, which extend along three directions: event summary, event drill-down and multi-events, (iii) the intelligent methods behind events visualization in the circumstance of heterogeneous data from IOT (internet of things) and web.
Intracellular Calcium Oscillations in Astrocytes: A Highly Plastic, Bidirectional Form of Communication between Neurons and Astrocytes In Situ

The spatial–temporal characteristics of intracellular calcium ([Ca2+]i) changes elicited in neurons and astrocytes by various types of stimuli were investigated by means of confocal fluorescent microscopy in acute rat brain slices loaded with the Ca2+ indicator indo-1. Neurons and astrocytes from the visual cortex and CA1 hippocampal region were identified in situ on the basis of their morphological, electrophysiological, and pharmacological features. We show here that stimulation of neuronal afferents triggered periodic [Ca2+]i oscillations in astrocytes. The frequency of these oscillations was under a dynamic control by neuronal activity as it changed according to the pattern of stimulation. After repetitive episodes of neuronal stimulation as well as repetitive stimulation with a metabotropic glutamate receptor agonist, astrocytes displayed a long-lasting increase in [Ca2+]i oscillation frequency. Oscillating astrocytes were accompanied by repetitive [Ca2+]i elevations in adjacent neurons, most likely because of the release of glutamate via a tetanus toxin-resistant process. These results reveal that [Ca2+]i oscillations in astrocytes represent a highly plastic signaling system that underlies the reciprocal communication between neurons and astrocytes.
Using MOEA to evolve a combinational circuit on a FPGA chip

A combinational circuit design method that can be completely implemented on a FPGA is presented. For carrying out faster evolution in evolutionary circuit design, a sub population based MOEA (multiobjective evolutionary algorithm) is employed in which the reconfigurable circuit (RC) architecture is encoded by Cartesian Genetic Programming (CGP). For hardware implementation, the Celoxica RC1000 PCI is employed which includes Xilinx Virtex xcv 2000E FPGA chip. This PCI card is communicating with host PC and acting as an evolvable platform. MOEA adopted modules are designed into a FPGA chip for discussing the rationality of circuit design method. Results of direct evolution and results of incremental evolution is compared, it shows MOEA is most efficient in the aspect of speeding up the convergence of evolution.
Import of Distributed Parameter Models into Lumped Parameter Model Libraries for the Example of Linearly Deformable Solid Bodies

Modelling of heterogeneous systems is always a trade-off between model complexity and accuracy. Most libraries of object-oriented, equation-based, multi-physical simulation tools are based on lumped parameter description models. However, there are different ways of including spatial dependency of certain variables in the model. One way that might be quite difficult is to manually discretize the model into an interconnection of lumped parameter models. This approach can get very time-consuming and is always sensitive to modelling or identification errors. To avoid these issues, we try to take advantage of the well-established methods for automatically discretizing a distributed parameter model for example by means of Finite Element methods. However, to achieve a suffiently good approximation, these methods very often result in large-scale dynamic systems that can not be handled within equation-based simulators. To overcome this drawback there exist different approaches within the literature. On the basis of deformable mechanical structures, one way of including distributed parameter models into libraries of lumped parameter models for the purpose of common simulation is pointed out in the present paper. For the implementation of the resulting models the authors take advantage of equation-based modelling libraries as new models can here easily be integrated.