Miracle-dz/UniFAR-FTUs huggingface dataset:
Group Routing: a Reliable Mutual Anonymous Approach in Dynamic Overlay

As an important component of online privacy, anonymity is concerned by all users of P2P system. Many methods are proposed to provide mutual anonymity and most of them are path-based: an anonymous path should be constructed by source peer before transmission. Although those proposals perform well in providing mutual anonymity, the pre-constructed paths suffer from node churn and make anonymous transmission unreliable. In this paper, we propose Group Routing (GR), an approach which is based on Onion Routing, to provide reliability as well as mutual anonymity. In GR, every stage of the pre- constructed path contains several nodes to be redundancies each others, and the messages are encrypted and split into several packages to be forward to destination in the path. Compared with previous approaches that focus on reliability of anonymous communication, GR takes advantage of higher reliability and anonymity. We demonstrate the effectiveness of GR through theoretical analysis and simulations. The analytical and experimental results show GR is more efficient to other proposals.
Analysis of Financial Distress Prediction Models

The purpose of this study is to evaluate financial and non-financial variables using the bankruptcy prediction model. Considering Taiwan companies listed between 2001 and 2005, the estimation sample comprises 140 firms (70 failing and 70 non-failing), and the validation sample comprises 52 firms (26 failing and 26 non-failing). In contrast to previous studies, this paper provides a corporate governance index as non-financial variables to predict financial distress along with financial index. Logistic regression is applied to examine these samples for 3 year data prior to business failure. In the estimation sample, the indexes combining both financial and corporate governance indexes gave the most accurate predictions. In the validation sample, the financial variables yielded the most accurate predictions.
Biological markers of the effects of intravenous methylphenidate on improving inhibitory control in cocaine-dependent patients

Prior research points to the importance of psychostimulants in improving self-control. However, the neural substrates underlying such improvement remain unclear. Here, in a pharmacological functional MRI study of the stop signal task, we show that methylphenidate (as compared with placebo) robustly decreased stop signal reaction time (SSRT), an index of improved control, in cocaine-dependent patients (a population in which inhibitory control is impaired). Methylphenidate-induced decreases in SSRT were positively correlated with inhibition-related activation of left middle frontal cortex (MFC) and negatively with activation of the ventromedial prefrontal cortex (vmPFC) in whole brain linear regressions. Inhibition-related MFC but not vmPFC activation distinguished individuals with short and long SSRT in 36 demographically matched healthy individuals, whereas vmPFC but not MFC activation, along with improvement in SSRT, was correlated with a previously implicated biomarker of methylphenidate response (systolic blood pressure). These results implicate a specific neural (i.e., vmPFC) mechanism whereby stimulants improve inhibitory control. Altered ventromedial prefrontal activation and increased blood pressure may represent useful CNS and peripheral biomarkers in individualized treatment with methylphenidate for patients with cocaine dependence.
The many views of a process: Toward a process architecture framework for product development processes

A product or system development process is a kind of complex system, arguably even more complex than the system it produces. Yet, the models and tools used by systems engineers and program managers to plan and manage technical work—such as process flowcharts, Gantt charts, work breakdown structures, and text‐rendered procedures—are less sophisticated and capable than the ones used to design the product system. When used, the various process models are often challenged to incorporate and maintain synchronized program information—e.g., they may be created by different subgroups in a program and based on different assumptions, and they may diverge as a program proceeds. Recently, architecture frameworks (AFs) have been used to help manage the complexity in engineered systems. An AF provides a portfolio of views of a complex system, each of which describes it partially and in a format meaningful to its users and their particular needs. This paper proposes the application of AF concepts to the management of the work done to develop a complex system product. The pieces of work and their relationships constitute a complex process. A portfolio of integrated and synchronized views of a single process model would seem to be preferable to the current state—a number of disparate and uncoordinated management models. This paper introduces a new application of AFs to development processes and suggests this area as one for further research and development in the systems engineering community. © 2008 Wiley Periodicals, Inc. Syst Eng
Computational study of defects and heat transfer in gold nanostructures

Gold nanoparticles are promising tools for cancer therapy and cell imaging due to their non-toxicity, high heat conduction and tunable optical properties for the infraredvisible region. Nanoparticles production often involves thermal annealing, a process that changes the structure of the nanoparticle by mechanisms that are not yet well understood. For any of the biomedical applications, the nanoparticles are organically-coated to allow targeting and efficient uptake by cancer cells. Once the nanoparticles are inside the cell, their optical tunability allows the use of specific wavelengths strongly absorbed or scattered by the particles but poorly interacting with the medium to induce hyperthermia or obtain an image of the cell. In any case, the nanoparticle is expected to heat up. Although the propagation of heat is well understood at the macroscale, the details of the heat transfer at the nanoscale are still poorly understood. In this work, we use classical, equilibrium molecular dynamics simulations to create nanoparticles and investigate how their crystalline structure and the number and type of defects evolves as a function of annealing conditions. We use both analytical methods and classical non-equilibrium molecular dynamics simulations to investigate the effects of the particle size and the type of interface on the heat transfer properties of bare and organic-coated gold nanoparticles embedded in water. Water was chosen to mimic the cellular medium because it is the most abundant cellular component. Our simulations with a slab system of water and gold suggest that the material present at the interface between the gold and the water affects the heat transfer in the system. Moreover, our analytical calculations and computational results indicate that the heat transfer is dominated by the heat conduction in the medium for large nanoparticles, while for smaller nanoparticles the interface controls the overall heat propagation.
Beamforming Design and Relay Selection for Multiple MIMO AF Relay Systems with Limited Feedback

In this paper we consider a half-duplex multiple-input multiple-output (MIMO) cooperative amplify-and-forward (AF) relay network with multiple relay nodes. Firstly, we assume the channel state information (CSI) is available at all nodes to investigate the optimal source and relay beamforming vector design and relay selection. Based on this structure, a new scheme of limited feedback joint effective relay selection and beamforming vector design is proposed, which uses a new strategy to share channel information between relay and destination. This proposed scheme, which chooses the best relay and optimizes the beamforming vectors maximizing the received SNR, can significantly reduce the required number of feedback bits and maintain a suitable performance compared to the optimal non-practical solution. Simulation results show that our scheme approaches the performance of the scheme with full CSI assumption and outperforms conventional schemes, while having lower computational complexity and lower feedback delay. The cooperative diversity gain is also verified by the simulation result.
The Effect of the Change of Furnace Profile with the Increase in Furnace Volume on Operation

Based on the characteristics of the change of furnace profile with an increase in furnace volume, the effects of blast furnace profile on operation are investigated. The investigation is made by use of numerical simulation models that are integrated to evaluate the whole furnace state including hearth. First, the characteristics of the change of furnace profile with the increase in furnace volume are reviewed. Then, evaluation of the effects of furnace profile is made from the viewpoint of efficiency and stability of operation. The larger furnaces are advantageous to lowering a fuel rate, while stability against channeling at periphery is poor. In addition, as for furnace hearth life extension, the effect of furnace volume is discussed. As the furnace volume increases, the molten iron velocity at peripheral region of the hearth increases.
Fabrication and Doping Methods for Silicon Nano‐ and Micropillar Arrays for Solar‐Cell Applications: A Review

Silicon is one of the main components of commercial solar cells and is used in many other solar‐light‐harvesting devices. The overall efficiency of these devices can be increased by the use of structured surfaces that contain nanometer‐ to micrometer‐sized pillars with radial p/n junctions. High densities of such structures greatly enhance the light‐absorbing properties of the device, whereas the 3D p/n junction geometry shortens the diffusion length of minority carriers and diminishes recombination. Due to the vast silicon nano‐ and microfabrication toolbox that exists nowadays, many versatile methods for the preparation of such highly structured samples are available. Furthermore, the formation of p/n junctions on structured surfaces is possible by a variety of doping techniques, in large part transferred from microelectronic circuit technology. The right choice of doping method, to achieve good control of junction depth and doping level, can contribute to an improvement of the overall efficiency that can be obtained in devices for energy applications. A review of the state‐of‐the‐art of the fabrication and doping of silicon micro and nanopillars is presented here, as well as of the analysis of the properties and geometry of thus‐formed 3D‐structured p/n junctions.
On the Proper Use of Mass Accuracy in Proteomics*

Mass measurement is the main outcome of mass spectrometry-based proteomics yet the potential of recent advances in accurate mass measurements remains largely unexploited. There is not even a clear definition of mass accuracy in the proteomics literature, and we identify at least three uses of this term: anecdotal mass accuracy, statistical mass accuracy, and the maximum mass deviation (MMD) allowed in a database search. We suggest using the second of these terms as the generic one. To make the best use of the mass precision offered by modern instruments we propose a series of simple steps involving recalibration of the data on “internal standards” contained in every proteomics data set. Each data set should be accompanied by a plot of mass errors from which the appropriate MMD can be chosen. More advanced uses of high mass accuracy include an MMD that depends on the signal abundance of each peptide. Adapting search engines to high mass accuracy in the MS/MS data is also a high priority. Proper use of high mass accuracy data can make MS-based proteomics one of the most “digital” and accurate post-genomics disciplines.
Cyber and Physical Access Control in Legacy System Using Passwords

Passwords—secret combinations of symbols—play an important role in physical world security (e.g. watchword to prevent unauthorized entry into military forbidden area) from ancient times. With emergence and advance of digital com- puters and computer network, passwords are also widely adopted in cyber world security protection. In most applications, password protection stands on the fron- tier of cyber/physical security defense. Compromise of passwords might render the whole system insecure, and make thereafter sophisticated cryptography solution ineffective. However, secure management of a large number of random passwords is a great challenge to human brains. We propose a visual cryptography technique, which allows users to store and manage ciphertexts of randomly chosen passwords in mobile phone and decrypt them manually on demand. The stored passwords re- main confidential, even if the mobile phone is infected by spyware (Assume the spyware can capture phone screen, and monitor phone CPU and RAM). We also analyze the security and feasibility of proposed method. Leveraging on this tech- nique, we give a simple access control system based on passwords, which provides a low cost alternative solution for legacy system besides smart card based solution.
Recent and Recurrent Selective Sweeps of the Antiviral RNAi Gene Argonaute-2 in Three Species of Drosophila

Antagonistic host–parasite interactions can drive rapid adaptive evolution in genes of the immune system, and such arms races may be an important force shaping polymorphism in the genome. The RNA interference pathway gene Argonaute-2 (AGO2) is a key component of antiviral defense in Drosophila, and we have previously shown that genes in this pathway experience unusually high rates of adaptive substitution. Here we study patterns of genetic variation in a 100-kbp region around AGO2 in three different species of Drosophila. Our data suggest that recent independent selective sweeps in AGO2 have reduced genetic variation across a region of more than 50 kbp in Drosophila melanogaster, D. simulans, and D. yakuba, and we estimate that selection has fixed adaptive substitutions in this gene every 30–100 thousand years. The strongest signal of recent selection is evident in D. simulans, where we estimate that the most recent selective sweep involved an allele with a selective advantage of the order of 0.5–1% and occurred roughly 13–60 Kya. To evaluate the potential consequences of the recent substitutions on the structure and function of AGO2, we used fold-recognition and homology-based modeling to derive a structural model for the Drosophila protein, and this suggests that recent substitutions in D. simulans are overrepresented at the protein surface. In summary, our results show that selection by parasites can consistently target the same genes in multiple species, resulting in areas of the genome that have markedly reduced genetic diversity.
Computing Arithmetic Invariants of 3-Manifolds

Snap is a computer program for computing arithmetic invariants of hyperbolic 3-manifolds, built on Jeff Weeks's SnapPea and the number theory package Pari. Its approach is to compute the hyperbolic structure to very high prec ision, and use th is to find an exact description of the structure. Then the correctness of the hyperbolic structure can be verified, and the arithmetic invariants of Neumann and Reid can be computed. Snap also computes high precision numerical invariants such as volume, Chern–Simons invariant, eta invariant, and the Borel regulator.
Sensitivity of L-Band SAR Backscatter to Aboveground Biomass of Global Forests

Synthetic Aperture Radar (SAR) backscatter measurements are sensitive to forest aboveground biomass (AGB), and the observations from space can be used for mapping AGB globally. However, the radar sensitivity saturates at higher AGB values depending on the wavelength and geometry of radar measurements, and is influenced by the structure of the forest and environmental conditions. Here, we examine the sensitivity of SAR at the L-band frequency (~25 cm wavelength) to AGB in order to examine the performance of future joint National Aeronautics and Space Administration, Indian Space Research Organisation NASA-ISRO SAR mission in mapping the AGB of global forests. For SAR data, we use the Phased Array L-Band SAR (PALSAR) backscatter from the Advanced Land Observing Satellite (ALOS) aggregated at a 100-m spatial resolution; and for AGB data, we use more than three million AGB values derived from the Geoscience Laser Altimeter System (GLAS) LiDAR height metrics at about 0.16–0.25 ha footprints across eleven different forest types globally. The results from statistical analysis show that, over all eleven forest types, saturation level of L-band radar at HV polarization on average remains ≥100 Mg·ha−1. Fresh water swamp forests have the lowest saturation with AGB at ~80 Mg·ha−1, while needleleaf forests have the highest saturation at ~250 Mg·ha−1. Swamp forests show a strong backscatter from the vegetation-surface specular reflection due to inundation that requires to be treated separately from those on terra firme. Our results demonstrate that L-Band backscatter relations to AGB can be significantly different depending on forest types and environmental effects, requiring multiple algorithms to map AGB from time series of satellite radar observations globally.
Influence of Sulfur and Manganese Contents on Texture and Fish-Scale Resistance of DC03EK Cold-Rolled Enamel Steel

In the this paper, the compositions design with low carbon and addition of sulfur and manganese which can enhance fish-scale resistance by MnS as hydrogen trap was adopted to produce DC03EK cold-rolled enamel steel. The effect of sulfur and manganese contents on formability and fish-scale resistance of DC03EK cold-rolled enamel steel was investigated. Results show that yield strength, ultimate tensile strength, elongation, work hardening exponent and average plastic strain ratio of the steel with sulfur content of 0.024wt% and manganese content of 0.22wt% is 133 MPa, 310 MPa, 36.8%, 0.22 and 1.46, respectively, showing the well formability. And its hydrogen penetration time and diffusion coefficient is higher than 12 min and lower than 9.26×10-7 cm2/s, respectively, showing excellent fish-scale resistance. However, for the steel with sulfur content of 0.012wt% and manganese content of 0.12wt%, even though better formability is obtained, the fish-scale resistance is poor with hydrogen penetration time of 4.7 min and hydrogen diffusion coefficient of 2.36×10-6 cm2/s which is far from the expectation of steel for enamel.
The Correlations between Planetary Nebula Morphology and Central Star Evolution: Analysis of the Northern Galactic Sample

Northern Galactic planetary nebulae (PNs) are studied to disclose possible correlations between the morphology of the nebulae and the evolution of the central stars (CSs). To this end, we have built the best database available to date, accounting for homogeneity and completeness. We use updated statistical distances and an updated morphological classification scheme, and we calculate Zanstra temperatures for a large sample of PNs. With our study we confirm that round, elliptical, and bipolar PNs have different spatial distributions within the Galaxy, with average absolute distances to the Galactic plane of 0.73, 0.38, and 0.21 kpc, respectively. We also find evidence that the distributions of the CS masses are different across these morphological groups, although we do not find that CSs hosted by bipolar PNs are hotter, on average, than CSs within round and elliptical PNs. Our results are in broad agreement with previous analyses, indicating that round, elliptical, and bipolar PNs evolve from progenitors in different mass ranges and might belong to different stellar populations, as also indicated by the helium and nitrogen abundances of PNs of different morphology.
A 4.7 THz HEB QCL receiver for STO2

We report on a 4.7 THz heterodyne receiver designed for high resolution spectroscopy of the astronomically important neutral oxygen (OI) line at 4.745 THz. The receiver is based around a hot electron bolometer (HEB) mixer and quantum cascade laser (QCL) local oscillator. This receiver has been developed to fly on the Stratospheric Terahertz Observatory (STO-2), a balloon-borne 0.8 m telescope observing from an altitude of 44 km for 14 days or more. We measure a double sideband receiver noise temperature of 815 K (~ 7 times quantum noise) with a noise temperature IF bandwidth of 3.5 GHz. We describe the receiver performance expected in flight and outline novel approaches to QCL amplitude and frequency stabilization.
ROBUST EXTRACTION OF CONTROL-POINT PAIRS FOR ELASTIC REGISTRATION OF HIGH-RESOLUTION SATELLITE IMAGES

Image registration is the process of spatially fitting two images of the same scene acquired on different dates, from different viewpoints, and/or using different sensors. Image registration is required in a variety of applications, such as, in image fusion, 3D scene reconstruction, and multi-temporal analysis (i. e. natural disaster monitoring, urban change detection, etc.). See [1] for a comprehensive survey. A typical image registration process is accomplished by identifying so-called control points (CP) pairs, in the involved images. Through such control points it is possible to estimate the underlying geometrical transformations between the considered images. Accuracy in image registration is strongly tied to: a) the geometrical transformation considered, which should account for the relative geometric (possibly non-rigid) differences between the images, and b) the distribution of CPs over the images. The correct selection of the latter is primordial not only to gain in accuracy but also in efficiency: while two pair of CPs would suffice to perfectly overlap images of a flat terrain (since they may only differ in shift, scale and rotation), a large number of them will be necessary to capture the relative geometric difference between images of high-relief surfaces acquired from different viewing angles, requiring, thus, complex elastic transformations. In the absence of information about the type of terrain, the best (thought not efficient) solution is to regularly distribute CPs all over the images. However, when some information about the terrain profile is available, a more elaborated algorithm can help us to decide the density of CPs on each region of the image. In this paper we present an automatic method to extract control points for accurate registration of high-resolution images, such as Quickbird, Ikonos, etc. Our approach generates a minimal distribution of control points based on the relief information provided by digital terrain models (DTM), achieving significant speedup in the process without sacrificing accuracy.
SeaLab Advanced Information Retrieval

Information Retrieval is a well established interdisciplinary topic in which machine learning, computational linguistic, computer programming and data mining merge together. SLAIR stands for Sea Lab Advanced Information Retrieval and is an efficient software architecture that embeds these issues in a unique framework. SLAIR is expandable both from the data format and algorithm point of view. A pluggable notion of distance between documents drives the subsequent clustering/classification machinery, moreover SLAIR is explicitly designed to manage large scale text mining problems. The demo will be focused on the versatility of the framework, the main goal is to show how the different metrics provided by SLAIR can enhance clustering/classification ability and eventually lead to different views of the underlying textual data.
Efficient algorithms for prefix and general prefix computations on distributed shared memory systems with applications

The paper presents efficient scalable algorithms for performing prefix (PC) and general prefix (GPC) computations on a distributed shared memory, (DSM) system with applications. PC and GPC are generic techniques that can be used to design sequential and parallel algorithms for a number of problems from diverse areas (K. Arvind et al., 1995; V. Kamakoti and C. Pandurangan, 1992).