Miracle-dz/UniFAR-FTUs huggingface dataset:
Transition Matrix Monte Carlo Methods for Complex Systems

The aim of this thesis is to develop efficient transition matrix Monte Carlo simulation methods for complex systems(e.g., spin glasses) that enable one to construct the transition matrix from which the density of states is calculated with high accuracy. In this thesis, I explore a series of the transition matrix Monte Carlo techniques that are newly developed to generate the density of states with high accuracy for various systems that exhibit phase transitions. The Ising model and the Potts model are used to demonstrate the performance of each methods. Especially, the specific heat curve of the two-dimensional Ising model is evaluated and compared to the exact result as a stringent accuracy test in many cases. I extend the monovariate multicanonical transition matrix Monte Carlo method to a bivariate version for the calculation of the joint density of states which depends on the energy and a second variable associated with the order parameter. This bivariate version is applied to the Edward-Anderson spin glass model which is one of the most challenging model in the field of computer simulation. After presenting the theoretical basis of the transition matrix Monte Carlo method, I explain the regulated temperature method which populates the transition matrix by the Metropolis algorithm with continuously varying temperature according to a certain schedule. I introduce new techniques that can produce the optimized temperature schedule in the context of the two-dimensional Ising model. Next I proceed to present the multicanonical transition matrix Monte Carlo method in which the transition matrix is constructed through the multicanonical iteration procedure. Although this method itself is faster than other existing techniques such as the broad histogram method and Wang-Landau algorithm, its simulation speed can be further increased by the renormalization idea which utilizes the simulation results for a small system to obtain an accurate initial estimate of the density of states for a large system through the convolution procedures. Especially a novel procedure about how to apply the renormalization idea in multiple dimensions is presented. To study the critical behavior of the spin glasses, to my knowledge for the first time, I employ the bivariate multicanonical sampling to construct the transition tensor from which the joint density of states can be calculated with high accuracy. I introduce a calculation technique that transforms the massive transition tensor to a normal transition matrix to avoid the cumbersome manipulation of tensors. Using the joint density of states, Landau free energies, the probability distribution functions of spin overlap and Binder parameters are calculated. Contrary to the majority of the previous reports in the literature, the results of my method provide evidences that nonzero temperature phase transition occurs in the two-dimensional Ising spin glass. For the ±J Ising spin glass, the critical temperature
Review and Prospect for Information Flow Security Technology

With the rapid development of computer and network technology,their systems are also attacked increasingly.The conventional security mechanisms,such as access control,intrusion detection and encryption only focus on the controls of information release,without fully ensuring end-to-end security.By using information flow analysis in the system,we can ensure the legality of their information flow.This paper overviews the typical models of information flow and their corresponding analysis methods.It describes briefly the applications and comparisons of these methods.The paper also gives the future research directions for the analysis methods of information flow security.It concludes that the analysis methods of information flow are feasible to achieve the end-to-end information security.
Predicting the structural, electronic and mechanical properties of three-dimensional boron nitride foam containing sp, sp2 and sp3 hybridized bonds

A first-principles approach is utilized to systematically investigate the structural, electronic and mechanical properties from a new BN phase (denoted super-(BN)16). Super-(BN)16 contains sp, sp2 and sp3 hybridized bonds. It is mechanically stable, even though it is energetically unfavorable than c-BN, w-BN, yne-BN, and so on. Due to the different hybridization type and the B-N covalent bonds with ionic characteristics, super-(BN)16 has unequal bonds and bond angles in these equal space positions. The calculated electronic structure showed it is a semiconductor with a direct band gap of 1.94 eV. The electronic states in the region near Fermi level mainly come from the 2p orbitals of the sp hybridized B and N atoms. The elastic constants and moduli of this phase exhibit clear anisotropy and super-(BN)16 should have a low hardness and high ductility. Additionally, it can be obtained from nanosheets, nanotubes and nanoribbons of yne-BN family under pressure.
Statistical Graphics Design Principles And Practices

Thank you for downloading statistical graphics design principles and practices. Maybe you have knowledge that, people have look hundreds times for their chosen novels like this statistical graphics design principles and practices, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they juggled with some harmful virus inside their desktop computer.
Topic Detection and Tracking Review

Topic detection and tracking,as one of natural language processing technologies,is to detect unknown topic and track known topic from the information of news medium.Since its pilot research in 1996,several large-scale evaluation conferences have provided a good environment for evaluating technologies of recognition,collection and organization.As topic detection and tracking shares similar challenges with information retrieval,data mining and information extraction in abrupt and successive data,it has become a hot research issue in the field of nature language processing.This paper introduced the background,definition,evaluation and methods in topic detection and tracking,and explored its future development trend through analyzing current research.
Gas and grain chemical composition in cold cores as predicted by the Nautilus three-phase model

We present an extended version of the 2-phase gas-grain code NAUTILUS to the 3-phase modelling of gas and grain chemistry of cold cores. In this model, both the mantle and the surface are considered as chemically active. We also take into account the competition among reaction, diffusion and evaporation. The model predictions are confronted to ice observations in the envelope of low-mass and massive young stellar objects as well as toward background stars. Modelled gas-phase abundances are compared to species observed toward TMC-1 (CP) and L134N dark clouds. We find that our model successfully reproduces the observed ice species. It is found that the reaction-diffusion competition strongly enhances reactions with barriers and more specifically reactions with H2, which is abundant on grains. This finding highlights the importance to have a good approach to determine the abundance of H2 on grains. Consequently, it is found that the major N-bearing species on grains go from NH3 to N2 and HCN when the reaction-diffusion competition is accounted. In the gas-phase and before few 10^5 yrs, we find that the 3-phase model does not have a strong impact on the observed species compared to the 2-phase model. After this time, the computed abundances dramatically decrease due to the strong accretion on dust, which is not counterbalanced by the desorption less efficient than in the 2-phase model. This strongly constrains the chemical-age of cold cores to be of the order of few 10^5 yrs.
Grand Challenge Carbon feedbacks in the climate system

The land and ocean biogeochemical cycles are key components of the Earth’s climate system. The surface fluxes of many greenhouse gases and aerosol precursors are controlled by biogeochemical and physical processes and are sensitive to changes in climate and atmospheric composition. Most importantly, biogeochemical processes control atmospheric concentrations of the main greenhouse gases (CO2, CH4 and N2O). Plants, soils and permafrost on the land together contain at least five times as much carbon as the atmosphere, and the global ocean contains at least fifty times more carbon than the atmosphere. Based on the 2015 Global Carbon Budget estimates, since 1870, CO2 emissions from fossil fuel combustion have released about 400±20 GtC (Gigatonnes carbon) to the atmosphere, while land use change is estimated to have released an additional 145±50 GtC. Of these cumulative anthropogenic CO2 emissions, 230±5 GtC have accumulated in the atmosphere, while the ocean and land ecosystems have taken up 155±20 GtC and 160±60 GtC, respectively. Land and oceans are hence absorbing around half of the carbon emitted from human activity, significantly mitigating the build up of CO2 in the atmosphere and climate change. In the absence of these carbon sinks, current atmospheric CO2 would already be about twice the pre-industrial CO2 concentration with an associated global warming likely above 2°C. However, substantial uncertainty remains about the magnitude of these carbon sinks, how they currently operate, and whether they will continue to be as effective as climate changes. When climate models first included climatecarbon cycle feedbacks, they indicated the potential for these carbon sinks to be significantly weakened under global warming, accelerating atmospheric CO2 increases and hence global
Inferring the jet parameters of active galactic nuclei using Bayesian analysis of VLBI data with a non-uniform jet model

The physical parameters of the jets of active galactic nuclei observed with Very Long Baseline Interferometry (VLBI) are usually inferred from core-shift measurements or from the flux and size measured at the peak frequency of the synchrotron spectrum. Both methods are preceded by modelling the observed VLBI jet structure with simple Gaussian templates. Here we infer the jet parameters using an inhomogeneous jet model directly, bypassing the modelling of the source structure with a Gaussian template or image deconvolution. We apply Bayesian analysis to multifrequency VLBA observations of radio galaxy NGC 315 and find that its parsec-scale jet is well described by an inhomogeneous conical model. Our results favour an electron–positron jet. We also detect a component as a part of a counter jet. Its position implies the presence of an external absorber with a steep density gradient close (r = 0.1 pc) to the central engine.
How to Read and Interpret FTIR Spectroscope of Organic Material

Fourier Transform Infrared (FTIR) has been developed as a tool for the simultaneous and quantitative determination of organic components, including chemical bond, as well as organic content (e.g. protein, carbohydrate and lipid). However, until now, there is no further information for the detailed information in the FTIR peaks. The objective of this study was to demonstrate how to read and assess chemical bond and structure in the organic material. The analysis was then compared with the literatures. The step-by-step method on how to read the FTIR data was presented, including reviewing simple to the complex organic materials. This study is potential to be used as a standard information on how to read FTIR peaks in the biochemical and organic materials.
Nanostructuring materials using solution synthesis approach for high performance thermoelectric devices

열전소자의 성능지수를 향상시키기 위한 연구가 활발하게 진행되고 있으며 최근 몇 년간 나노크기의 입자를 만들거나 석출시켜 낮은 열전도도를 유도하는 연구를 통해 2.3 이상의 높은 열전성능지수를 얻을 수 있었다. 따라서 본 연구에서는 나노 사이즈의 금 입자를 화학적 방법으로 환원과 동시에 기존에 알려진 정공 타입의 Bi0.5Sb1. 5Te3 물질과 혼합하여 350℃에서 방전 플라즈마 소결과 450℃에서 열간압 소결을 통해 측정용 펠릿을 만들어 비교하였다. 금 입자의 함량이 증가 할수록 금 입자의 치환형 결함에 의한 정공 농도의 증가로 전기전도도가 증가하며 방전 플라즈마 소결의 경우 금 입자가 없는 화합물과 비교하여 전 온도 영역에서 높은 열전 성능지수인 0. 55를 얻을 수 있었다. 또한 방전 플라즈마 소결로 제작된 펠릿에서 나타나는 AuTe2 이차상과 더불어 내부 불순물에 의한 격자 열전도도의 감소를 확인 할 수 있었다. 방전 플라즈마 소결을 통해 제작한 펠릿은 가공을 통해 압력에 수직방향과 수평방향의 물성 차이를 측정하여 비교하였다. 또한 방전 플라즈마와 열간압에 의한 소결 결과물의 열전특성 차이를 분석하였다. 열간압에 의한 펠렛은 방전 플라즈마와 금 함량에 따라 비슷한 경향성을 보이지만 대체적으로 모든 열전성능에 있어서 우수한 성질을 가진다. 이는 방전 플라즈마 상에서 보이는 안티모니의 응집으로 인한 기저 상의 안티모니 부족으로 Bi0.5+xSb1.5-xTe3와 같은 조성을 가지게 되어 나타나는 것으로 생각 할 수 있다. 두 번째로 콜로이드 용액 합성을 통한 바텀 업 방법의 접근을 하였다. argyrodite 계열의 결정인 Ag8SnSe6의 콜로이드 나노 입자를 새로운 방법으로 더욱 싸고 간편하게 합성하여 높은 결정성을 가지는 나노크리스탈을 얻을 수 있었다. 특히 원료물질로 AgCl, Sn(Ⅱ)Cl2•2H2O, SeO2와 같은 새로운 조합의 물질을 사용하여 불순물을 제거하고 상대적으로 빠르고 낮은 온도에서 합성을 진행하였다. 또한 기존의 논문으로 알려진 Ag8SnS6의 합성방법을 수정하여 2 가지 argyrodite 계열 물질의 특성을 비교하였고 이를 통해 열전소자로 이용 가능성을 제시하였다. ⓒ 2016 DGIST
The updated luminosity correlations of gamma-ray bursts and cosmological implications

Several interesting luminosity correlations among gamma-ray burst (GRB) variables have been recently discussed extensively. In this paper, we derive the six luminosity correlations ($\tlag-L$, $V-L$, $\epkk-L$, $\epkk-E_\gamma$, $\trt-L$, $\epkk-E_{\gamma, \mathrm{iso}}$) from the light curves and spectra of the latest 116 long GRBs, including the time lag ($\tlag$) between low and high photon energy light curves, the variability ($V$) of the light curve, the peak energy of the spectrum ($\epkk$), and the minimum rise time ($\trt$) of the peaks. We find that the intrinsic scatter of the $V-L$ correlation is too large and there seems no inherent correlation between the two parameters using the latest GRB data. The other five correlations indeed exist when the sample is enlarged. The $\epkk-E_\gamma$ correlation has a significantly lower intrinsic scatter compared to the other correlations. We divide the full data into four redshift bins when testing possible evolution of the correlations with redshift. We find no statistically significant evidence for the redshift evolution of the luminosity correlations. To avoid the circularity problem when constraining the cosmological parameters, we simultaneously minimize $\chi^2$ with respect to both correlation parameters $a$, $b$ and the cosmological parameters using the maximum likelihood method. For the flat $\Lambda$CDM, the best fit is $\omm=0.31^{+0.13}_{-0.10}$. We also constrain the possible evolution of the equation of state (EOS) of the dark energy using the GRBs together with the Union2 compilation of SNe Ia and the $H(z)$ data. The result is consistent with the cosmological constant at $2 \sigma$ confidence level and mainly due to the GRB data, the dark energy EOS shows slight deviation from -1 at $z \geq0.5$ as was persistently presented with many previous data sets.
Microstructure Development during Low-Current Resistance Spot Welding of Aluminum to Magnesium

Resistance spot welding of aluminum (Al5754) to magnesium (AZ31B) alloys results in the formation of a variety of solidification microstructures and intermetallic compounds that may affect the in-service performance of the weld. This study evaluates the relationship between the welding parameters and the properties of the weld nugget that is formed, and clarifies the morphological and microstructural evolutions within the weld regions during the low-current “small-scale” resistance spot welding of Al5754 to AZ31B. The investigations included a combination of microstructural characterization and thermodynamic analysis of the weld region. The results show that the welding time and clamping force parameters have significant effects on the properties of the nugget formed. The optimal welding parameters were found to be 300 ms welding time and 800 N clamping force. Weld nuggets formed with lower welding time and clamping force were undersized and contained extensive porosity. Meanwhile, a clamping force above 800 N caused gross deformation of the test samples and the expulsion of the molten metal during the welding process. The most significant microstructural changes occurred at the weld/base metal interfaces due to the formation of Al17Mg12 and MgAl2O4 intermetallic compounds as well as significant compositional variation across the weld pool. The thermal gradient across the weld pool facilitated the formation of several microstructural transitions between equiaxed and columnar dendrites.
An SMT Approach To A Multiparty Economic Scheduling Problem

We discuss a multiparty resource allocation problem in a digital marketplace for purchase and sale of compute resources. The problem exhibits several challenging characteristics: (i) multiple agents and resources in a single matching instance, (ii) constraints that can be imposed on individual resources or a combination of resources, and (iii) short wall clock time for production settings. We model the problem as a satisfiability problem, and discuss an implementation using the Z3 SMT solver.
Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context

A new channel estimation based on compressive sensing(CS) in non-contiguous orthogonal frequency division multiplexing(NC-OFDM) system was proposed.As for NC-OFDM systems in cognitive radio context,the infrastructure of CS-based channel estimation,the design of pilot patterns and the algorithm of channel estimation were explored.Es-pecially,a criterion of optimizing pilot pattern in the CS-based channel estimation was proposed by minimizing the mu-tual coherence of the measurement matrix in CS theory.Simulations show that,under many patterns of deactivated sub-carriers,CS-based channel estimation obtains much better performance than existing NC-OFDM channel estimation methods in terms of the mean square error of the channel estimate as well as the bit error rate of the system.
GRAVITATIONAL POTENTIAL ENVIRONMENT OF GALAXIES. I. SIMULATION

We extend the concept of galaxy environment from the local galaxy number density to the gravitational potential and its functions like the shear tensor. For this purpose, we examine whether or not one can make an accurate estimation of the gravitational potential from an observational sample which is finite in volume, biased due to galaxy biasing, and subject to redshift space distortion. Dark halos in a ΛCDM simulation are used in this test. We find that one needs to stay away from the sample boundaries by more than 30 h−1 Mpc to reduce the error within 20% of the rms values of the potential or the shear tensor. The error due to the galaxy biasing can be significantly reduced by using the galaxy mass density field instead of the galaxy number density field. The error caused by the redshift space distortion can be effectively removed by correcting galaxy positions for the peculiar velocity effects. We inspect the dependence of dark matter halo properties on four environmental parameters: local density, gravitational potential, and the ellipticity, and prolateness of the shear tensor. We find that the local density has the strongest correlation with halo properties. This is evident that the internal physical properties of dark halos are mainly controlled by small-scale physics. In high-density regions dark halos are on average more massive and spherical and have higher spin parameter and velocity dispersion. We also study the relation between the environmental parameters and the subtypes of dark halos. The spin parameter of satellite halos depends only weakly on the local density for all mass ranges studied, while that of isolated or central halos depends more sensitively on the local density. The gravitational potential and the shear tensor have weaker correlations with halo properties, but have environmental information independent of the local density.
Fracture properties of alkali activated mortars

In this paper, three different coal fly ash-based alkali activated mortars are studied. The three different mortars are obtained using the same binding system but different types (i.e. silica sand or expanded perlite) and sizes of aggregates. Small-scale beams are constructed together with additional specimens for material characterization. The small-scale beams are notched and loaded in a three-point bend setup to investigate the fracture properties of the three mixtures. The setup utilized follows the draft of the ACI 446 report on the fracture testing of concrete. The fracture energy is determined from the work of fracture and results highly dependent on the type of aggregate rather than its dimension. Digital image correlation is employed to obtain the displacement and therefore strain components on the side surface of the specimens in order to investigate the crack propagation and determine the size of the fracture process zone, which appears to be similar to the one of a cement-based mortar.
Optical trapping and single molecule measurement technologies for the investigation of biomolecular forces and motion

Author(s): Wilcox, Jamianne | Advisor(s): Valentine, Megan T. | Abstract: Intracellular transport along microtubules is a process critical to cell health, andone whose breakdown is associated with neurodegenerative disorders. In this thesis, wedescribe new technologies that will enable and improve investigations of multiple typesof intracellular transport on microtubules.Although the single molecule properties of many motor proteins have been well characterized,their behavior when transporting biological cargoes as a group of motors is stillnot well understood due to measurement challenges, as well as a lack of a model systemfor systematically studying collective motor behavior in vitro. In this work, we discussthe construction of an optical trapping setup capable of applying and measuring forceswith 2 pN accuracy. We report our design of a biomimetic droplet system that reproducesthe relevant surface properties of biological cargoes while allowing the droplets tobe used as optical trapping probes. We also present a new optical trapping calibrationtechnique that allows experimenters to utilize the nonlinear range of the trapping forceprofile, and thereby measure the high forces developed by groups of motor proteins.Finally, we investigate the distributions of diffusion coeffcients found for MicrotubuleAssociated Proteins diffusing on microtubules through Monte Carlo simulations, andexamine the subtleties of interpreting and reporting single molecule diffusion data.
Wildlife GUARDSS: Using Uncertain Real-Time Information in Signaling Games for Sustainability

Mobile sensors, e.g., unmanned aerial vehicles (UAVs), are becoming increasingly important in security domains and can be used for tasks such as searching for poachers in conservation areas. Such mobile sensors augment human patrollers by assisting in surveillance and in signaling potentially deceptive information to adversaries, and their coordinated deployment could be modeled via the well-known security games framework. Unfortunately, real-world uncertainty in the sensor’s detection of adversaries presents major challenges in the sensors’ use. This leads to signiﬁ-cant detriments in security performance. We ﬁrst discuss the current shortcomings in more detail, and then propose a novel game model that incorporates uncertainty with sensors. We then brieﬂy introduce GUARDSS, the algorithm to solve these games, and show results from a simulation based on a real-world deployment of a conservation sys-tem in South Africa.