Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithms for efficient data management of component-based applications in cloud environments

Cloud environments face a growing demand for application hosting, and applications consisting of multiple data-sources and storage components. The need to ensure service level agreements for these types of applications creates important challenges for cloud infrastructure providers. The main contribution of this paper is an optimal cost-effective model and two algorithms to map component-based data oriented applications to cloud platforms. The first algorithm is based on an Integer Linear Programming formulation and minimizes an objective function, taking into account the capacities of the available nodes and links, as well as the customer requirements. This algorithm is able to obtain the optimal solution, but shows a limited scalability. For this reason a heuristic algorithm is designed to solve the scalability issue. The experimental results thoroughly compare the execution times and obtained node usage for both algorithms.
An Experimental Test of the Effects of Social Conflict on Posttraumatic Stress Symptoms and Alcohol Craving

While substantial efforts have been devoted to understanding links between posttraumatic stress disorder (PTSD) and hazardous alcohol use, relatively little research has examined possible third factor variables that may maintain this comorbidity. Social conflict is common among people suffering from posttraumatic stress symptoms (PTSS), hazardous alcohol use, and the combination of these two conditions, and is thought to maintain both PTSS and hazardous alcohol use. Fortunately, social conflict is malleable, but there is little evidence to date examining social conflict as a common maintaining factor. The current study investigated the effect of social conflict on state PTSS, alcohol craving, and alcohol approach bias in an effort to isolate one portion of a complex constellation of difficulties. A total of 46 participants with a history of trauma exposure and current hazardous alcohol use completed a laboratory-based assessment of posttraumatic stress symptom reactions, alcohol craving, and alcohol approach bias in response to social conflict, as manipulated via the script-driven imagery procedure. Results demonstrated that social conflict, compared to a neutral social script, elicited an increase in state PTSS symptoms, but not in alcohol craving, or alcohol approach bias. Sex was not demonstrated to have a moderating effect on social conflict as it relates to PTSS, alcohol craving, or alcohol approach bias. These findings highlight the role of social conflict in eliciting state PTSS; however, contrary to hypotheses social conflict did not elicit alcohol craving or approach bias. Possible reasons for these findings as well as limitations and future directions are discussed. Acknowledgements The research project reported in this dissertation document was supported by the Ruth L. Kirschstein National Research Service Award training fellowship, award number F31AA022828, and the National Institute on Alcohol Abuse and Alcoholism. The content of this document represents the views of the author, and does not necessarily represent the official views of the National Institutes of Health. Dedication This dissertation is dedicated all of my family and friends who have supported me throughout this process. Thank you to Libby, Mark, and Kim who welcomed us in to their family and made Arkansas home. Thank you to Beth, Craig, Caroline, and Thomas for your love and support over the last 6 years. To my amazing parents and sister who have loved me and supported me through many years of school, I wouldn't be where I am without you! Thank you to my very patient husband for your unwavering love and support. Thank you to my faculty mentor, lab mates, and my cohort who have encouraged me and facilitated my growth as a professional. Without each of you, this would never have been possible. This dissertation is dedicated to all of you. Table of
The Data Vortex Optical Packet Switched Interconnection Network

A complete review of the data vortex optical packet switched (OPS) interconnection network architecture is presented. The distributed multistage network topology is based on a banyan structure and incorporates a deflection routing scheme ideally suited for implementation with optical components. An implemented 12-port system prototype employs broadband semiconductor optical amplifier switching nodes and is capable of successfully routing multichannel wavelength-division multiplexing packets while maintaining practically error-free signal integrity (BER < 10-12) with median latencies of 110 ns. Packet contentions are resolved without the use of optical buffers via a distributed deflection routing control scheme. The entire payload path in the optical domain exhibits a capacity of nearly 1 Tb/s. Further experimental measurements investigate the OPS interconnection network's flexibility and robustness in terms of optical power dynamic range and network timing. Subsequent experimental investigations support the physical layer scalability of the implemented architecture and serve to substantiate the merits of the data vortex OPS network architectural paradigm. Finally, modified design considerations that aim to increase the network throughput and device-level performance are presented.
Energy radiated from a fluctuating selfdual string

We compute the energy that is radiated from a fluctuating selfdual string in the large-N limit of AN−1 theory using the AdS-CFT correspondence. We find that the radiated energy is given by a non-local expression integrated over the string world-sheet. We also make the corresponding computation for a charged string in six-dimensional classical electrodynamics, thereby generalizing the Larmor formula for the radiated energy from an accelerated point particle.
Residential exposure to aircraft noise and hospital admissions for cardiovascular diseases: multi-airport retrospective study

Objective To investigate whether exposure to aircraft noise increases the risk of hospitalization for cardiovascular diseases in older people (≥65 years) residing near airports. Design Multi-airport retrospective study of approximately 6 million older people residing near airports in the United States. We superimposed contours of aircraft noise levels (in decibels, dB) for 89 airports for 2009 provided by the US Federal Aviation Administration on census block resolution population data to construct two exposure metrics applicable to zip code resolution health insurance data: population weighted noise within each zip code, and 90th centile of noise among populated census blocks within each zip code. Setting 2218 zip codes surrounding 89 airports in the contiguous states. Participants 6 027 363 people eligible to participate in the national medical insurance (Medicare) program (aged ≥65 years) residing near airports in 2009. Main outcome measures Percentage increase in the hospitalization admission rate for cardiovascular disease associated with a 10 dB increase in aircraft noise, for each airport and on average across airports adjusted by individual level characteristics (age, sex, race), zip code level socioeconomic status and demographics, zip code level air pollution (fine particulate matter and ozone), and roadway density. Results Averaged across all airports and using the 90th centile noise exposure metric, a zip code with 10 dB higher noise exposure had a 3.5% higher (95% confidence interval 0.2% to 7.0%) cardiovascular hospital admission rate, after controlling for covariates. Conclusions Despite limitations related to potential misclassification of exposure, we found a statistically significant association between exposure to aircraft noise and risk of hospitalization for cardiovascular diseases among older people living near airports.
Reliable communications in aerial sensor networks by using a hybrid antenna

An AWSN composed of bird-sized Unmanned Aerial Vehicles (UAVs) equipped with sensors and wireless radio, enables low cost high granularity three-dimensional sensing of the physical world. The sensed data is relayed in real-time over a multi-hop wireless communication network to ground stations. The following characteristics of an AWSN make effective multi-hop communication challenging - (i) frequent link disconnections due to the inherent dynamism (ii) significant inter-node interference (iii) three dimensional motion of the UAVs. In this paper, we investigate the use of a hybrid antenna to accomplish efficient neighbor discovery and reliable communication in AWSNs. We propose the design of a hybrid Omni Bidirectional ESPAR (O-BESPAR) antenna, which combines the complimentary features of an isotropic omni radio (360 degree coverage) and directional ESPAR antennas (beamforming and reduced interference). Control and data messages are transmitted separately over the omni and directional modules of the antenna, respectively. Moreover, a communication protocol is presented to perform fast neighbor discovery and beam steering. We present results from extensive simulations then consider three different real-world AWSN application scenarios and empirical aerial link characterization and show that the proposed antenna design and protocol reduces the packet loss rate, as compared to a single omni or ESPAR antenna.
Functional Delaunay Reenement

Given a complex of vertices, constraining segments (and planar straight-line constraining facets in 3D) and an-Lipschitz control spacing function f() over the domain, an algorithm presented herein can generate a conforming mesh of Delaunay triangles (tetrahedra in 3D) whose circumradius-to-shortest-edge ratios are no greater than p 2 (2 in 3D). The triangle (tetra-hedron) size is within a constant factor of f(). An implementation in 2D demonstrates that the algorithm generates excellent mesh.
Computational modeling of the thermal conductivity of single-walled carbon nanotube–polymer composites

A computational model was developed to study the thermal conductivity of single-walled carbon nanotube (SWNT)–polymer composites. A random walk simulation was used to model the effect of interfacial resistance on the heat flow in different orientations of SWNTs dispersed in the polymers. The simulation is a modification of a previous model taking into account the numerically determined thermal equilibrium factor between the SWNTs and the composite matrix material. The simulation results agreed well with reported experimental data for epoxy and polymethyl methacrylate (PMMA) composites. The effects of the SWNT orientation, weight fraction and thermal boundary resistance on the effective conductivity of composites were quantified. The present model is a useful tool for the prediction of the thermal conductivity within a wide range of volume fractions of the SWNTs, so long as the SWNTs are not in contact with each other. The developed model can be applied to other polymers and solid materials, possibly even metals.
Relationships between leaf lifespan and structural defences in a low-nutrient, sclerophyll flora

Summary 1. The spectrum between species with low leaf mass per area (LMA), short-lived leaves and high photosynthetic rate to those with high LMA, long-lived leaves and low photosynthetic rate is one of the major spectra of variation between plant species, and is of particular relevance to the ‘carbon-gain strategy’ of plants. 2. In this study the relationship between physical properties of leaves and their lifespan was quantified for 17 sclerophyllous species from a nutrient-poor woodland in eastern Australia. Fracture properties of leaves (force of fracture, tissue toughness) and other leaf traits [LMA, thickness, dry-matter content (DMC), leaf area] were measured for each species and evaluated as predictors of leaf lifespan in cross-species and phylogenetic analyses, and for intercorrelation with one another. 3. The LMA, mean force of fracture, leaf thickness and leaf area each explained approximately 30‐40% of variation in leaf lifespan. Leaf toughness explained 25% of variation in leaf lifespan, and DMC 12%. Leaf toughness and DMC were correlated with each other, but not with leaf thickness. Leaf thickness and toughness were related closely to LMA, while DMC and LMA were only marginally correlated. 4. Nutrients can be withdrawn prior to leaf death and redeployed elsewhere in the canopy when leaf death is initiated by a plant. However, when control is external to the plant these nutrients are lost. There may be advantages to increasing defence to give a high likelihood that the plant has control over the timing of leaf death.
Sense and sensibility in personalized e‐commerce: How emotions rebalance the purchase intentions of persuaded customers

This research develops and tests a theoretical model of customer persuasion in personalized online shopping, building on information processing theory, and addressing cognitive and affective stages of the persuasion process. Data from 582 experienced online customers were used to validate the proposed model through structural equation modeling and multigroup analysis. Results show that quality of personalization, message quality, and benefits of the personalized recommendations are important in the persuasion process. Positive emotions increase the effect of persuasion on purchase intentions, contrary to negative emotions. The study extends online personalization theory, offers an in-depth analysis of the persuasion process in online shopping, and provides valuable recommendations for personalized online marketing.
Syntactic structure feature analysis and classification method research

Characteristics and difficulties of Chinese natural language processing, as well as the appropriate language to deal with the basic resources relative lack of some mature foreign technology and research results can not be applied directly to the Chinese question answering system. To this end, the question answering system for Chinese facts, presents a new extraction algorithm based on the characteristics analysis of syntactic structure and classification of the answer, the answer extraction problem as a classification of the candidate answers, upcoming candidate answer classified as correct and error categories. First, the method according to the types of problems corresponding to the type of candidate answers extracted from the text fragments candidate answer in the sentence simple features and syntactic structure characteristics; then take advantage of these features of the training classifier; trained classifier to distinguish the candidate answer for the correct answer.
CLASSIFICATION OF CUSTOMERS EMOTION USING NAÏVE BAYES CLASSIFIER (Case Study: Natasha Skin Care)

Today customers can easily submit their review or opinion of a product or a service from Natasha Skin Care through mentions tweet @NatashaSkinCare. Mentions can be identified emotions of costumers after using a products or a services of Natasha Skin Care. This research proposes to classify emotions according to Ekman that is joy, surprise, anger, fear, sad, and disgust by using Naive Bayes Classifier. Naive Bayes Classifier is chosen because of its advantages that is simple, fast, and high accuracy. The dataset in this study amounted to 19,253 with the division for each class is 804 joy, 43 surprise, 154 anger, 61 fear, 287 sad, 167 disgust, and 17736 no-emotions. The results show that the Naive Bayes Classifier method has a good performance to classify the emotions Natasha Skin Care customers through twitter. The average accuracy rate on the no-emotions class dataset is 80.19%. The average of the emotional classification without involving the no-emotions class shows the highest recall value in the joy class of 92.21%. The highest precision value in the surprise class was 97.77% and the highest F1-Measure was in the joy class of 89.14%. The mean on the dataset with the no-emotions class is 88.58%. Although the accuracy of the dataset with the no-emotions class is higher, the precision and recall value is very low, which is 0%. After using the ROS resampling algorithm, the mean values of precision, recall, and F1-Measure are highest in the no-emotions class. Precision value is 96.64%, recall value is 76.36%, and F1-Measure value is 85.93%. Keyword: emotional classification, naive bayes classifier, resampling
Munc18c Depletion Selectively Impairs the Sustained Phase of Insulin Release

OBJECTIVE The Sec1/Munc18 protein Munc18c has been implicated in Syntaxin 4–mediated exocytosis events, although its purpose in exocytosis has remained elusive. Given that Syntaxin 4 functions in the second phase of glucose-stimulated insulin secretion (GSIS), we hypothesized that Munc18c would also be required and sought insight into the possible mechanism(s) using the islet β-cell as a model system. RESEARCH DESIGN AND METHODS Perifusion analyses of isolated Munc18c- (−/+) or Munc18c-depleted (RNAi) mouse islets were used to assess biphasic secretion. Protein interaction studies used subcellular fractions and detergent lysates prepared from MIN6 β-cells to determine the mechanistic role of Munc18c in Syntaxin 4 activation and docking/fusion of vesicle-associated membrane protein (VAMP)2-containing insulin granules. Electron microscopy was used to gauge changes in granule localization. RESULTS Munc18c (−/+) islets secreted ∼60% less insulin selectively during second-phase GSIS; RNAi-mediated Munc18c depletion functionally recapitulated this in wild-type and Munc18c (−/+) islets in a gene dosage-dependent manner. Munc18c depletion ablated the glucose-stimulated VAMP2–Syntaxin 4 association as well as Syntaxin 4 activation, correlating with the deficit in insulin release. Remarkably, Munc18c depletion resulted in aberrant granule localization to the plasma membrane in response to glucose stimulation, consistent with its selective effect on the second phase of secretion. CONCLUSIONS Collectively, these studies demonstrate an essential positive role for Munc18c in second-phase GSIS and suggest novel roles for Munc18c in granule localization to the plasma membrane as well as in triggering Syntaxin 4 accessibility to VAMP2 at a step preceding vesicle docking/fusion.
Hierarchical Data Association Framework with Occlusion Handling for Multiple Targets Tracking

The problem of tracking multiple targets in video is addressed, and a novel hierarchical data association framework with occlusion handling is presented. The association hierarchy first divides the detections, targets, and candidates into several disjoint branches, then progressively associates the detections to the targets and candidates within each branch, and finally initializes the targets through candidate upgrade. Furthermore, the depth disorder inference and targets motion pairing prediction are introduced to explicitly tackle target-target and target-environment occlusions, respectively. Experiments verify that our method improves the runtime performance significantly while keeping competitive tracking accuracy and precision compared with several state-of-the-art methods.
Combination network coding: Alphabet size and zigzag decoding

Combination network coding can be regarded as a generalization of Maximum Distance Separable (MDS) code. An existing bound on the required alphabet size for MDS code is generalized for combination network coding. Besides, a class of combination network code called Zigzag-Decodable (ZD) code is considered. It involves only exclusive-OR and bit-shifting operations and can be decoded by a fast algorithm called zigzag decoding. It was proved that the ZD code has lower encoding and decoding complexities than other existing codes, at the expense of slight rate loss.
Texture Replacement Using Color-Coded Garments Submission

In this paper we present a video processing algorithm for texture replacement of moving garments. We use a colorcoded pattern which encodes texture coordinates within a local neighborhood in order to determine the geometric deformation of the texture. A time-coherent texture interpolation is obtained by the use of 3D radial basis functions. Shading maps are determined with a surface reconstruction technique and applied to new textures which replace the color pattern in the video sequence. Our method enables editing and even completely exchanging fabric pattern designs of garments worn by actors as a video post-processing step.
Lagrangian Coherent Structures with Guaranteed Material Separation

Given an unsteady flow field, one common way to compute Lagrangian Coherent Structures (LCS) is to extract extremal structures of the Finite Time Lyapunov Exponent (FTLE). Experience has shown that the resulting structures are often close to material structures (i.e., material lines or material surfaces). Moreover, it has been proven that for an integration time converging to infinity, they converge to exact material structures. However, due to the finite integration time in FTLE, they are generally not exact material structures.
A 3 D Electroactive Polypyrrole-Collagen Fibrous Scaffold for Tissue Engineering

Fibers that can provide topographical, biochemical and electrical cues would be attractive for directing the differentiation of stem cells into electro-responsive cells such as neuronal or muscular cells. Here we report on the fabrication of polypyrrole-incorporated collagen-based fibers via interfacial polyelectrolyte complexation (IPC). The mean ultimate tensile strength of the fibers is 304.0 ± 61.0 MPa and the Young’s Modulus is 10.4 ± 4.3 GPa. Human bone marrow-derived mesenchymal stem cells (hMSCs) are cultured on the fibers in a proliferating medium and stimulated with an external electrical pulse generator for 5 and 10 days. The effects of polypyrrole in the fiber system can be OPEN ACCESS Polymers 2011, 3 528 observed, with hMSCs adopting a neuronal-like morphology at day 10, and through the upregulation of neural markers, such as noggin, MAP2, neurofilament, β tubulin III and nestin. This study demonstrates the potential of this fiber system as an attractive 3D scaffold for tissue engineering, where collagen is present on the fiber surface for cellular adhesion, and polypyrrole is encapsulated within the fiber for enhanced electrical communication in cell-substrate and cell-cell interactions.