Miracle-dz/UniFAR-FTUs huggingface dataset:
An Econometric Analysis of the Volatility Risk Premium

This paper examines the volatility risk premium, defined as the difference between expected future volatility under the risk-neutral measure and the expectation under the physical measure. This risk premium represents the price of volatility risk in financial markets. In order to compute this risk premium, one must be able to accurately measure volatility under both measures. It is standard to use the VIX volatility index is used to proxy the expectation under the risk-neutral measure. Estimation under the physical measure is less straightforward. Using ultra-high-frequency transaction data on SPDR, the S&P500 ETF, we implement a novel approach for estimating integrated volatility on the frequency domain which allows us to isolate the biases from microstructure noise from the true volatility process. Once we compute the volatility risk premium, we perform a comprehensive econometric analysis of its determinants before, during, and after the Financial Crisis. The results indicate that the volatility risk premium is very sensitive to liquidity and distress in the financial system. We are able to link this statistical relationship to a recent literature in financial economics dealing with intermediation and liquidity provision in the options markets.
RNAi-mediated gene silencing of vascular endothelial growth factor C suppresses growth and induces apoptosis in mouse breast cancer in vitro and in vivo

Vascular endothelial cell growth factor (VEGF)-C promotes tumorigenesis by allowing lymph node metastasis and lymphangiogenesis, among other actions. RNA interference (RNAi) is a novel technique for suppressing target gene expression and may increase the effectiveness of cancer treatments. The present study assessed the influence of VEGF-C RNAi on the apoptosis and proliferation of mouse breast cancer cells in vitro and in vivo. A total of three pairs of small interfering RNA (siRNA) targeting mouse VEGF-C were designed and synthesized prior to transfection into 4T1 cells via a liposomal approach. Reverse transcription polymerase chain reaction, western blot analysis, a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, Hoechst 33258 staining and flow cytometry were performed in vitro to analyze VEGF-C expression, cleaved caspase-3 protein expression and 4T1 cell proliferation and apoptosis. Experiments were also conducted in vivo on BALB/c mice with breast cancer. Tumor weight and volume were measured and the number of apoptotic cells in tumor tissues was assessed by a TUNEL assay. Immunohistochemical assays and an enzyme-linked immunosorbent assay were used to measure the expression of VEGF-C in tumor tissues. The results demonstrated that the three pairs of siRNA, particularly siV2, significantly reduced VEGF-C mRNA and protein levels in 4T1 cells. siV2 was deemed to be the most efficient siRNA and therefore was selected to be used in subsequent experiments. Furthermore, in vitro studies indicated that VEGF-C RNAi significantly decreased cell growth, induced apoptosis and upregulated the expression of cleaved caspase-3 protein. Tumor weight and volume in breast cancer in vivo models was reduced by the intratumoral injection of siV2. Antitumor efficacy was associated with decreased VEGF-C expression and increased induction of apoptosis. The present study therefore indicated that VEGF-C RNAi inhibited mouse breast cancer growth in vitro and in vivo and that it may be a novel targeted therapy for breast cancer.
Linux Capabilities : making them work

Linux capabilities have been partially implemented for many years, and in their incomplete state have been nearly unusable. In light of recent kernel developments, including VFS support and per-process support for bounding-set and secure-bits, capabilities have finally come of age. In this paper we demonstrate, with examples, how capabilities enhance the security of the modern Linux system.
Leveraging Degradation Testing and Condition Monitoring for Field Reliability Analysis With Time-Varying Operating Missions

Traditionally, degradation testing and condition monitoring are used separately to investigate field reliability. Barriers are naturally formed between these two types of methods due to condition-discrepancies between lab testing and field monitoring, as well as time-varying missions among product population groups. In this paper, a joint framework for field reliability analysis is presented by integrating degradation testing data as well as mission operating information with condition monitoring observations. A coherent modeling strategy is introduced for the information integration by gradually adopting random effects, dynamic covariates, and marker processes into a baseline stochastic degradation model. In detail, random effects are introduced to cope with the inherent unit-to-unit variation. Dynamic covariates are adopted to deal with the external condition heterogeneity. Marker processes are used to account for the time-varying missions. To facilitate information integration and reliability analysis, the Bayesian method is used to implement parameter estimation and degradation analysis. The reliability assessment of products' populations, degradation prediction, and residual life prediction of individual products are investigated. Finally, an illustrative example for field degradation analysis of oil debris in a lubrication system of a machine tool's spindle system is presented. The effectiveness of information integration and the capability of degradation inference are demonstrated through this example.
Infection with CagA-Positive Helicobacter Pylori Strain Containing Three EPIYA C Phosphorylation Sites is Associated with More Severe Gastric Lesions in Experimentally Infected Mongolian Gerbils (Meriones Unguiculatus)

Infection with Helicobacter pylori strains containing high number of EPIYA-C phosphorylation sites in the CagA is associated with significant gastritis and increased risk of developing pre-malignant gastric lesions and gastric carcinoma. However, these findings have not been reproduced in animal models yet. Therefore, we investigated the effect on the gastric mucosa of Mongolian gerbil (Meriones unguiculatus) infected with CagA-positive H. pylori strains exhibiting one or three EPIYA-C phosphorilation sites. Mongolian gerbils were inoculated with H. pylori clonal isolates containing one or three EPIYA-C phosphorylation sites. Control group was composed by uninfected animals challenged with Brucella broth alone. Gastric fragments were evaluated by the modified Sydney System and digital morphometry. Clonal relatedness between the isolates was considered by the identical RAPD-PCR profiles and sequencing of five housekeeping genes, vacA i/d region and of oipA. The other virulence markers were present in both isolates (vacA s1i1d1m1, iceA2, and intact dupA). CagA of both isolates was translocated and phosphorylated in AGS cells. After 45 days of infection, there was a significant increase in the number of inflammatory cells and in the area of the lamina propria in the infected animals, notably in those infected by the CagA-positive strain with three EPIYA-C phosphorylation sites. After six months of infection, a high number of EPIYA-C phosphorylation sites was associated with progressive increase in the intensity of gastritis and in the area of the lamina propria. Atrophy, intestinal metaplasia, and dysplasia were also observed more frequently in animals infected with the CagA-positive isolate with three EPIYA-C sites. We conclude that infection with H. pylori strain carrying a high number of CagA EPIYA-C phosphorylation sites is associated with more severe gastric lesions in an animal model of H. pylori infection.
The use of SPOT VEGETATION data in a classification tree approach for burnt area mapping in Australian savanna

An algorithm to map burnt areas has been developed for SPOT VEGETATION (VGT) data in Australian woodland savannas. A time series of daily VGT images (15 May to 15 July 1999) was composited into 10-day periods by applying a minimum value criterion to the near-infrared band (0.78-0.89 @m). The algorithm was developed using a classification tree methodology that was confirmed as a powerful means of image classification. This methodology allowed the identification of three classes of burnt surfaces that appear to be differentiated by the proportion of the pixel that is burnt, the intensity of the fire and the density of the tree layer. The performance of the algorithm was assessed by classification of one VGT composite image (31 May-9 June) using, as representative of the ground truth, burnt areas extracted from two Landsat TM scenes (9 June). We randomly extracted 30 windows (each of ∼14 km by 14 km) for which we compared the percentage of area burnt as derived from TM and VGT. The estimated mean absolute deviation in the percentage of the area burnt in each window is - 6.3%. In the area common to the two datasets a total amount of 6473 km 2 was estimated to be burnt in the VGT classification against 7536 km 2 that was burnt according to TM images. The accuracy of the classification was found to vary with the vegetation type being the most accurate estimate in low woodland with an underestimation error of 8.6%. These results show that VGT could be a very useful sensor for burnt area mapping over large woodland areas, although the low spatial resolution and the lack of a thermal band can be a limitation in certain conditions (e.g. understorey burns). The same methodology will be applied to map burnt areas for the entire Australian continent.
Stereotype-based semantic expansion for image retrieval

We present a novel, stereotype-based semantic expansion approach to identify various image sets that stereotypically represent different aspects of a given keyword. Specifically, given an adjective keyword query, our method expands it to a set of noun sub-keywords, which are stereotypical examples that can be described by the given adjective (e.g., “cute” to “{infant, kitten, .}”). We also perform a similar process for noun keywords with adjectives (e.g., “infant” to “{cute, sweet, .}”). To perform such expansion, we use Google Books n-grams, a new corpus of 500 million books. We harvest stereotypical relationships among nouns and adjectives by utilizing useful lexical patterns such as similes on n-grams. To demonstrate benefits of our method, we have applied our method to text-based image retrieval. Our method shows a diverse set of images given tested keywords. According to a small scale user study with 12 participants, our method shows a higher recall ratio of what a user wants to find, compared to returning images only from original keywords.
Two-way coupled structural acoustic optimization via model order reduction (MOR)

A reduced order model is developed for low frequency, fully coupled, undamped and constantly damped structural acoustic analysis of interior cavities, backed by flexible structural systems. The reduced order model is obtained by applying a Galerkin projection of the coupled system matrices, from a higher dimensional subspace to a lower dimensional subspace, whilst preserving some essential properties of the coupled system. The basis vectors for projection are computed efficiently using the Arnoldi algorithm, which generates an orthogonal basis for the Krylov subspace containing moments of the original system. A computational test case is analyzed, and the computational gains and the accuracy compared with the direct method in ANSYS. Further, the reduced order modelling technique is applied to a two-way coupled vibro-acoustic optimization problem, with stacking sequences of the composite structure as design variables. The optimization is performed via a hybrid search strategy combining outputs from Latin Hypercube Sampling (LHS) and Mesh Adaptive Direct Search (MADS) algorithm. It is shown that reduced order modelling technique results in a very significant reduction in simulation time, while maintaining the desired accuracy of the optimization variables under investigation.
Efficient Modified Blom Scheme for Key Management in Wireless Sensor Networks

Security is an inevitable part in this world. Security plays an important role for applications of WSNs due to the vulnerability of the network. Key management has become one of the main requirements in the field concerned with security of sensor network. Key is required for establishing a secure communication link between the nodes ready for transmitting data. Due to increased interests in sensor network, establishing a secure link between communicating nodes has become a prime area of concern. In this paper we have discussed one of the prominent key management schemes, its modified version and then proposed our own computation efficient key management scheme.
Ripple current effect on output power of solar-cell panel

To investigate the ripple current on the output power of solar cells, a testing system is set up to draw triangular currents with different ripples from a solar-cell panel by a boost converter operating from 10 kHz to 100 kHz. The dynamic characteristics of the solar-cell panel are analyzed based on the measured current and voltage waveforms. Experimental results indicate that the output voltage lags to some degree as the output current is higher than that at the maximum power point (MPP), leading to deterioration in the output power. This problem can be alleviated by adding a filter capacitor at the output of the solar-cell panel or increasing the operating frequency of the power converter.
A scalability study of interconnect architectures for System-on-Chip

Network-on-Chip (NoC) architectures were proposed to solve scalability issues experienced in bus-based SoCs. They incorporate a communication infrastructure defined by topology, routers and switches, in order to provide a scalable and high performance network for the SoC resources while satisfying the constraints of embedded platforms. The choice of appropriate NoC topology depends on the desired network size for the required performance. Simulation of NoCs based on real application traffic is time consuming, and therefore not a feasible approach for rapid design space exploration. In this paper, a methodology to study the scalability of three on-chip interconnect architectures, WK-recursive, Mesh and Spidergon, is presented. Simulation results are presented for different cases, demonstrating the potential of our approach for selecting the most scalable on-chip interconnect architecture.
On content-based image synthesis

We develop a content-based image synthesis software to compose a novel picture from many existing pictures. Text labels and user drawn sketches are provided to retrieve desired pictures for composing. We add text labels to images according to image features, so that our search by text labels can generate accurate results. Shape features are used to exclude pictures that do not match the user drawn sketches. We also improve the interactive image segmentation to be more automatic. We apply seamless blending techniques to compose pictures.
Research in a Conflict Zone : Grassroots Diplomacy in Darfur

This paper outlines a research framework to assess attitudes towards peace and conflict and support a form of “grassroots diplomacy” in conflict and post-conflict societies. Based on research in Darfur conducted in 2007-2008, a combination of methods that can be effective tools for addressing this challenge is detailed. The intent is to provide a framework that others interested in research in conflict areas can implement in different scenarios. Disciplines Communication | International and Area Studies Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License. This report is available at ScholarlyCommons: http://repository.upenn. edu/cgcs_publications/13 Public Opinion Research in a Conflict Zone: Grassroots Diplomacy in Darfur An occasional paper from the Center for Global Communication Studies with the Stanhope Centre for Communications Policy Research Authors: Iginio Gagliardone Nicole Stremlau With a foreword by: Simon Haselock
Fighting Poverty Together: Rethinking Strategies for Business, Governments, and Civil Society to Reduce Poverty

Chapter 1: Fighting Poverty PART I: FAILURE OF THE LIBERTARIAN APPROACH Microcredit Misses its Mark Mirage at the Base of the Pyramid Romanticizing the Poor PART II: FIGHTING POVERTY Selling Beneficial Goods to the Poor Employment is the Solution More Government, Please Social Entrepreneurship: Beyond the Hype
Improving channel utilization by restricting data traffic access in voice-video-data integration for high capacity wireless channels

A medium access control (MAC) protocol for integrating voice, videoconferencing and email data packet traffic in a high capacity wireless channel while at the same time ensuring the high priority of video and voice is presented and investigated. By combining our past and new scheduling ideas with an idea recently introduced in the literature, the results of our formerly published work are significantly improved. We evaluate, via simulations and comparisons with other protocols in the recent literature, the performance of the protocol and we focus on the impact of different types and loads of data traffic on the system performance.
Treatment of Rules in Individual Metadata of Flexible Contents Management

The properties of contents stored in a computer system are very wide while the data volume treated in the system becomes very large. It is important to treat each stored object in different manners to reject its properties in the data management for the large amount of stored data. To satisfy the requirement, we propose a method for the autonomous management based on ECA rules stored in metadata of the contents. We study the feasibility of treating a large number of ECA rules corresponding to the number of stored objects. Because the cost for evaluating conditions in the rules becomes dominant to the system perfornzance when the number of objects increases, we divide the conditions into two types, previously evaluable conditions and nuttime evaluable conditions, and construct a discrimination network for the previously evaluable conditions of each event to reduce the cost for processing the rules. We implement the methods in the autonomous disk system, a high functional storage system we proposed, and evaluate the eficiency of them.
Understanding service demand for adaptive allocation of distributed resources

Internet services experience frequent changes in demand, resource characteristics and service requirements. A service can meet its requirements with minimal cost only if the allocation of its distributed resources can be adaptively controlled. The design of adaptive control schemes requires a solid understanding of the dynamic characteristics of the distributed service, demand and resources. This study examines the dynamic properties of distributed demand and differs from prior demand characterization work by focusing on dynamic variations across clients, time and region which are crucial in adaptively allocating distributed resources. Our analysis of the demand for the 1998 World Cup web site finds that the dynamic behavior of a small subset of clients is representative of the entire demand, the churn in the active set of clients from day to day is relatively small and that regional demand shows significant, and predictable, variations in the hourly scales. These results will provide guidance for the design of adaptive policies.
Model-based integration of visual cues for hand tracking

We present a model based approach to the integration of multiple cues for tracking high degree of freedom articulated motions and apply it to the problem of hand tracking using a single camera sequence. Hand tracking is particularly challenging because of occlusions, shading variations, and the high dimensionality of the motion. The novelty of our approach is in the combination of multiple sources of information which come from edges, optical flow and shading information. In particular, we introduce in deformable model theory a generalized version of the gradient-based optical flow constraint, that includes shading flow i.e., the variation of the shading of the object as it rotates with respect to the light source. This constraint unifies the shading and the optical flow constraints (it simplifies to each one of them, when the other is not present). Our use of cue information from the entirety of the hand enables us to track its complex articulated motion in the presence of shading changes. Given the model-based formulation, we use shading when the optical flow constraint is violated due to significant shading changes in a region. We use a forward recursive dynamic model to track the motion in response to 3D data derived forces applied to the model. The hand is modeled as a base link (palm) with five linked chains (fingers) while the allowable motion of the fingers is controlled by recursive dynamic constraints. Model driving forces are generated from edges, optical flow and shading. The effectiveness of our approach is demonstrated with experiments on a number of different hand motions with shading changes, rotations and occlusions of significant parts of the hand.
Design and Implementation of MicrostripLowpass-Bandpass Diplexer on FR-4 Substrate

The purpose of this paper is to design a lowpass-bandpass diplexer printed on FR-4 substrate. The matching circuit design of a lowpass-bandpass diplexer may be a challenge in conventional designs because a wideband (from zero frequency to approximately the cutoff frequency of the lowpass filter) open condition is required to achieve in bandpass channel circuit. This paper proposes a new lowpass-bandpass diplexer that involves using a simple matching design that can easily meet the required matching condition in each channel circuit. For the lowpass channel, the simulated in-band insertion loss and cutoff frequency are less than 0.1dB and approximately 1.5 GHz, respectively. For the bandpass channel, the simulated minimal insertion loss and center frequency are approximately 3.2dB and 2.4GHz respectively. The simulated isolation between the two operating bands is approximately 32 dB. The tested insertion loss of the lowpass filter and bandpass filter is 3.2dB and 8.92dB respectively. The tested isolation between the two operating bands is approximately 40dB.
Graph Based Microscopic Images Semi and Unsupervised Classification and Segmentation

In this paper, we propose a general formulation of discrete functional regularization on weighted graphs. This framework can be used to on any multi-dimensional data living on graphs of arbitrary topologies. But, in this work, we focus on the microscopic image segmentation and classification with a semi and unsupervised schemes. Moreover, to provide a fast image segmentation we propose a graph based image simplification as a pre-processing step. Biological elements contained in images such as cells, cytoplasm and nuclei are segmented and classified with this image simplification and the label diffusion processes on weighted graphs. Keywords— Discrete regularization, weighted graphs, microscopical images, image simplification, semi-supervised, unsupervised, segmentation, classification.