Miracle-dz/UniFAR-FTUs huggingface dataset:
La curva de rendimientos a plazo y las expectativas de tasas de interés en los mercados colombianos de renta fija 2002-2007

Como se incorporan las expectativas de las tasas de interes en la estructura de tipos de interes en Colombia? Las dos principales teorias propuestas son la Hipotesis de las Expectativas (HE) y la Hipotesis de prima por liquidez (HPL). Este estudio contrasta ambas teorias, tanto para las tasas de los TES como las de los CDTs, empleando modelos econometricos de series de tiempo que se controlan por la persistencia de las tasas y su heterocedasticidad. Los resultados soportan la HPL, consistente con el hecho de que en Colombia las tasas de largo plazo tienden a ser mayores que las de corto plazo. De otro lado, las tasas de largo plazo presentan algun poder predictivo sobre las tasas futuras de corto plazo, consistente con la HE.
A Multiple-FPGA Parallel Computing Architecture for Real-time Simulation of Deformable Objects

In recent years there has been a growing interest in computer-based surgical planning, virtual-reality enabled training of medical procedures, and computer gaming all involving non-rigid deformable objects. High-fidelity simulations of haptic interaction with deformable objects is computationally demanding. The Finite Element Method (FEM) is known to produce relatively accurate solution for continuum mechanics-based models of soft-object deformation. Linear elastic FE models require solving a large sparse system of equations. The solution accuracy can be improved by increasing the resolution of the finite element mesh resulting in a larger number of equations and hence greater computational complexity. Depending on the mechanical characteristics of the soft-object, to maintain stability and high fidelity in haptic interaction, the update rate should be in the range of 1001000Hz. This, for example, means that for a moderately-sized three-dimensional mesh of 6000 nodes, a set of 18000 linear equations must be solved within 1-10ms. In this thesis, hardware-based parallel computing is proposed for finite-element (FE) analysis of soft-object deformation models. In particular, a distributed implementation of the (CG) algorithms on N Field Programmable Gate Array (FPGA) devices connected in a ring configuration is developed. This Parallel architecture can be utilized to solve the large system of equations arising from FE models at iii high update rates required for stable haptic interaction. Massive parallelization of the computations is achieved by customizing the hardware architecture to the problem at hand and employing a large number of adaptive fixed-point computing units in parallel. The proposed hardware architecture satisfies three important criteria: (i) it meets the haptic rendering timing constraint by enabling an update rate of 400Hz; (ii) it attempts to simulate as many nodes as possible, given the available resources on the FPGA devices employed in this work and (iii) it is scalable both within an FPGA and also across multiple FPGA devices. This research builds upon our group’s earlier work in [1]. In that paper a novel highly parallelized single-FPGA architecture was proposed for solving system of equations arising from FEM using Conjugate gradient method. In this thesis, a multiple-FPGA architecture based on that design has been proposed. The contributions in the new multiple-FPGA design can be summarized as follows. • proposing a novel method for expansion of conjugate gradient (CG) algorithm to multi processors. • a new sparse matrix by vector multiplication unit, performing as the kernel of our hardware-based CG solver. • proposing a novel storage format (SMVIS) for storing a vector, pre-multiplied by an sparse matrix which tremendously reduces the memory required vector storage. • developing a new memory architecture for storing vectors in the CG algorithm, making the design capable of performing vector operations in the CG
Nanocrystalline Silicon Thin Film Transistors on Optically Clear Polymer Foil Substrates

We have fabricated TFTs of nanocrystalline silicon (nc-Si) at 150°C on clear polymer substrates (coefficients of thermal expansion, α~45 to 55ppm/K), on Kapton® 200E (α=17ppm/K), and on Corning 1737 glass (α=3ppm/K) for comparison. Because thermally stable polymers, such as Kapton® 200E polyimide, have glass transition temperatures as high as 325°C, they are candidates for direct substitution of display glass. The stresses developed in the substrate and device layers, due to α, are reduced by decreasing the thickness of the active layers, by cutting the layers into islands separated by exposed substrate, and by designing stresses, via plasma conditions, into the SiNx passivating layers. By using these three techniques we have made nc-Si TFTs on high Tg, and high α, clear polymer foils with electron mobilities of up to 18cm 2 /Vs. When integrated with bottom-emitting organic light emitting diodes, such devices will allow for a 10x reduction in pixel TFT areas, compared to TFTs of amorphous silicon.
Physical Modeling and Scaling Properties of 4H-SiC Power Devices

4H silicon carbide (4H-SiC) has great potential for use as a material for power devices owing to its superior electrical properties. The distinctive feature of 4H-SiC is the high avalanche breakdown field and its anisotropy. In order to realize 4H-SiC power devices that make the best use of the excellent physical properties, device simulation, considering anisotropic physical properties is indispensable. This paper reports on the modeling of anisotropic impact ionization coefficients for device simulation, and the effect of anisotropic impact ionization coefficients on the avalanche breakdown of 4H-SiC power devices. We show that the avalanche breakdown voltage is degraded due to the anisotropy of impact ionization coefficients, which is caused by the lateral field at the termination structure. In addition, we precisely evaluate the effect of the high avalanche breakdown field of 4H-SiC on the performance of power devices. Scaling theory is applied for the design of power devices. A new figure of merit (HFOM) is derived as an invariant of scale transformation, which is a function of avalanche breakdown field and regarded as a measure of the performance of the power device.
Enhancing WLAN MAC Protocol performance using Differentiated VOIP and Data Services Strategy

The application of Voice over-IP (VoIP) over WLANs has drawn a lot of attention from both industry and academia. Currently, the highly dense deployment of WLANs results in that the number of stations in a Basic Service Set (BSS) increases quickly, and thus the work on the capacity for VoIP is becoming a new research hot point. For many of today’s 802.11 MAC implementations, the 802.11e requires a HW upgrade. However, replacing existing 802.11 HW devices to provide QoS is costly, and hence may not be desirable to many WLAN owners, especially, hotspot service providers with a huge number of deployed APs. In recent years, various methods have been proposed to improve the capacity for VoIP in WLANs, and they can be divided into two approaches. Enhance the efficiency of VOIP in MAC layer Differentiate VoIP and data services The first approach is achieved by header compression and frame aggregation.This strategy requires modification to existing protocols, and cannot be supported by current devices. This paper considers only the second method. It proposes a simple software upgrade based solution, called an Extended Dual queue Scheme (EDQ), to provide QoS to real-time services such as VoIP. The extended dual queue scheme operates on top of the legacy MAC. EDQ does not require any WLAN device hardware (HW) upgrade.
Crop Insurance Savings Accounts

This research explores the viability of an alternative design for crop insurance based upon farmer-owned savings accounts that are regulated, monitored, and marginally assisted by the government. Such accounts could be an effective risk management tool for many farmers and could operate without major government subsidization. Relative to the current program, the proposed design should exhibit minimal moral hazard and adverse selection problems, and since farm-level risk does not have to be priced, the proposed design eliminates the premium rating difficulties that weaken actuarial soundness and trigger the need for substantial external subsidies. In addition, administrative costs should be considerably lower. (This abstract was borrowed from another version of this item.)
Optimal sampling of visual information for lightness judgments

The variable resolution and limited processing capacity of the human visual system requires us to sample the world with eye movements and attentive processes. Here we show that where observers look can strongly modulate their reports of simple surface attributes, such as lightness. When observers matched the color of natural objects they based their judgments on the brightest parts of the objects; at the same time, they tended to fixate points with above-average luminance. When we forced participants to fixate a specific point on the object using a gaze-contingent display setup, the matched lightness was higher when observers fixated bright regions. This finding indicates a causal link between the luminance of the fixated region and the lightness match for the whole object. Simulations with rendered physical lighting show that higher values in an object’s luminance distribution are particularly informative about reflectance. This sampling strategy is an efficient and simple heuristic for the visual system to achieve accurate and invariant judgments of lightness.
Social Discrete Choice Models

Human decision making underlies data generating process in multiple application areas, and models explaining and predicting choices made by individuals are in high demand. Discrete choice models are widely studied in economics and computational social sciences. As digital social networking facilitates information flow and spread of influence between individuals, new advances in modeling are needed to incorporate social information into these models in addition to characteristic features affecting individual choices. In this paper, we propose two novel models with scalable training algorithms: local logistics graph regularization (LLGR) and latent class graph regularization (LCGR) models. We add social regularization to represent similarity between friends, and we introduce latent classes to account for possible preference discrepancies between different social groups. Training of the LLGR model is performed using alternating direction method of multipliers (ADMM), and training of the LCGR model is performed using a specialized Monte Carlo expectation maximization (MCEM) algorithm. Scalability to large graphs is achieved by parallelizing computation in both the expectation and the maximization steps. The LCGR model is the first latent class classification model that incorporates social relationships among individuals represented by a given graph. To evaluate our two models, we consider three classes of data to illustrate a typical large-scale use case in internet and social media applications. We experiment on synthetic datasets to empirically explain when the proposed model is better than vanilla classification models that do not exploit graph structure. We also experiment on real-world data, including both small scale and large scale real-world datasets, to demonstrate on which types of datasets our model can be expected to outperform state-of-the-art models.
Recognition Essential Protein Based on Multi Parameters Combination

For the low recognition degree of essential protein based on topological parameter, the correlation between the essentiality of proteins and their main topological parameters is analyzed and the nature of the essentiality-judgment ability of the parameters is explored firstly. Then, the mutual information of essential node these parameters contain is brought out in virtue of their correlation, based on which the construction method of combined parameter is put forwards. In deeper study, the recognition degree of a combined parameter is found to have close relations not only to the performances of the independent parameters it constructed from, but also to the correlation between these independent parameters, and a asynchronous algorithm based on parameters combination is proposed lastly. The results of the emulation are not only consistent to each other highly, but also show that the performance of the method is better than that of the others obviously.
Common Ground, Common Future: Moral Agency in Public Administration, Professions, and Citizenship

The Moral Agent, Moral Organization, and the Public Administrator What Is a Moral Agent? The Special Ethical Aspects of Public Organizations Citizenship and Public Administration The Ethical Environment of Public Administration The Need for Ethical Reasoning in Public Administration Moral Agency, the Public Administrator, and the Private Citizen Moral Agency in the Public Sector The Ideal Public Administrator The Legislator's Moral Agency Conflicts of Obligations Bending and Breaking the Rules Moral Whistle-Blowing The Ideal and the Real Ethical Breakdowns in Public Administration Insufficient Commitment Excessive Commitment to Goals Moral Dilemmas The Public Administrator as Strong Evaluator Ethics in Business CSR Opponents of CSR Proponents of CSR Discussion Perspectives on Government Conclusion Managed Care Origins and Structure of Managed Care Moral Challenges of Managed Care Alternative Perspectives on Managed Care The Legal Profession The Client's Interest and the Interests of Justice Moral Obligations Common to the Legal Profession The Legal Profession and Public Service Civil Law Attorneys Committed to Causes Conclusion Higher Education Ethics in the Academy: Level 1 Ethics in the Academy: Level 2 University-Government Partnerships University-Business Partnerships Intercollegiate Athletics Conclusion Unifying Ethical Theory Traditional Ethical Theories The Unity of the Absolutist Theories The Kantian Legislator in the Kingdom of Ends and the Moral Agent The Unified Ethic, Communitarianism, and Individualism Rawls and the Unified Ethic Applying the Unified Ethic to Moral Agency The Moral Agent as Morally Responsible Citizen Insufficient Commitment to Moral Values Transformation and Reconfiguration Moral Agency in Business Use of Foreign, Low-Wage Labor Should Tobacco Companies Exist? The Moral Exemplarship of the Private Executive Moral Agency and the Attorney Encouraging the Process of Moral Agency in the Health Professions Higher Education in the Context of the Kingdom of Ends The Public Agent as Exemplar for the Private Professional: A Dialogue Points of Agreement Geuras: The Public Administrator as Citizen Exemplar Model Does Not Fully Apply to the Private Sector Garofalo's Response Summary Common Ground, Common Future Introduction Requirements for Reform Conclusion
Intrinsic Factors Contributing to Axon Regeneration in the Mammalian Nervous System

Introduction The success or failure of neural circuit rewiring through axon regeneration depends on the interplay between two main determinants. The injured neurons must synthesize structural components for outgrowing processes and activate signal transduction pathways to sense and decode guidance cues. At the same time, the surrounding microenvironment must provide suitable substrates and information to promote and direct axon elongation. Although there is general agreement that both neuronal and environmental factors are responsible for the poor outcome of brain repair, over the past decades attention has been mainly focused on the latter aspect. In particular, the observation that adult central nervous system (CNS) neurites can elongate into the growth-permissive peripheral nervous system (PNS) environment (Bray and Aguayo, 1989), together with the discovery that myeli-nating oligodendrocytes express neurite growth-inhibitory proteins (Schwab et al., 1993), have led to the notion that central neurons may be capable of regrowing their axons, but they fail because of adverse environmental conditions. Accordingly, in recent years an expanding set of growth-inhibitory molecules and related signal-ing pathways have been described in the CNS milieu (e. observations indicate that the intrinsic properties of the affected neurons are also crucial to determine the result of repair processes. Different types of nerve cells, when confronted with the same environment, show remarkably variable regenerative capabilities, from growth cone formation The strength of regenerative phenomena is tightly related to the activity of a set of neuronal genes associated with growth cone function and process elongation (Fawcett, 2001; Fawcett et al., 2001; Fernandes and Tetzlaff, 2001). The ability for up-regulating such genes in response to injury is not equal among central neurons (Herdegen et al. As a consequence, the neutralization of major inhibitory cues may result scarcely effective, if not accompanied by the activation of intrinsic neuritic growth mechanisms (Fischer et al., 2004a,b). These observations indicate that removal of extrinsic inhibition may be important , but it is not sufficient to achieve CNS repair. On the other hand, it is also clear that in adult neurons the molecular machinery required to sustain neuritic growth is not constitutively active, but it is subject to strict control mechanisms, the nature and biological meaning of which are still unclear. In this chapter, current knowledge about the role of intrinsic factors in axon regeneration will be reviewed, and the main mechanisms that regulate their expression and function described. Finally, the physiological significance of neuritic growth control in …
Cerebral aneurysm perforations complicating therapy with Guglielmi detachable coils: a meta-analysis.

BACKGROUND AND PURPOSE The risk of intraprocedural aneurysm perforation in patients with previously ruptured aneurysms tends to be higher than that of patients with previously unruptured aneurysms, but a statistically significant difference has not been shown. Our purpose was to define the rates of occurrence and of morbidity and mortality associated with aneurysmal perforation associated with coil embolization. METHODS A meta-analysis of the results from 17 published retrospective reports of aneurysm perforations complicating therapy with Guglielmi detachable coils (GDCs) was performed. Rates of perforation and associated morbidity and mortality in previously ruptured and unruptured aneurysms were calculated. The mechanism of perforation was noted. RESULTS The risk of intraprocedural perforation was significantly higher in patients with ruptured aneurysms compared with patients with unruptured aneurysms (4.1% vs 0.5%; P <.001). The combined risk of permanent neurologic disability and death associated with intraprocedural aneurysm perforation was 38% for ruptured aneurysms and 29% for unruptured aneurysms. The morbidity and mortality rates with perforations caused by coils (39%) and microcatheters (33%) were similar. The morbidity and mortality rate for microguidewire perforations was considerably lower (0%, n = 4) than the rates for coils and microcatheters, but number of cases was too low to indicate statistical significance. CONCLUSION The risk of aneurysm perforation during GDC therapy is much higher in patients with previously ruptured aneurysms than in those with unruptured aneurysms. The morbidity and mortality rates are substantial for perforations caused by coils and microcatheters, whereas they seem to be much lower for perforations caused by microguidewires.
Classification of Flowers : A Symbolic Approach Y H

In this work, we propose a skeleton based approach to classify flower images. Flowers are segmented using whorl based region merging segmentation. Skeleton of a flower is obtained from the segmented flower using a skeleton pruning method. The distance features are extracted from the skeleton endpoints and junction points. The features are normalized using discrete cosine transform. The reduced features are aggregated and represented in the form of an inter-valued type data and are stored in the knowledgebase. A symbolic classifier has been explored for the purpose of classification. To corroborate the efficacy of the proposed method, an experiment is conducted on our own data set of 30 classes of flowers, containing 3000 samples. The data set has different flower species with similar appearance (small inter-class variations) across different classes and varying appearance (large intra-class variations) within a class. In addition, the images of flowers are of different poses, with cluttered background under different lighting and climatic conditions. An experiment has been conducted by picking images randomly from the database and it is shown that relatively a good performance can be achieved, using symbolic classifier.
Spectrum Efficient Single-Sideband Single-Carrier with Frequency-Domain Equalization

In this paper, a novel spectrum efficient single-sideband single-carrier (SC) with frequency-domain equalization (SSB-FDE) using amplitude shift keying (ASK) modulation (ASK SSB-FDE) is proposed. Similar to the conventional SC transmission with FDE (SC-FDE), the ASK modulated symbol block to be transmitted is transformed by discrete Fourier transform (DFT) into frequency-domain signal. Then, inverse DFT (IDFT) is applied to the upper (or lower) sideband spectrum to obtain the time-domain SSB signal block. The cyclic prefix (CP) inserted SSB signal block is transmitted over a frequency-selective fading channel. At a receiver, the minimum mean square error (MMSE) based FDE is applied. ASK SSB-FDE has lower peak-to-average power ratio (PAPR) and better throughput performance than QAM SC-FDE when the throughput is plotted as a function of peak transmit SNR. This is confirmed by computer simulation assuming a frequency-selective Rayleigh fading channel.
A Weighted Support Vector Clustering Algorithm and its Application in Network Intrusion Detection

Network Intrusion detection is an area that has received much attention in recent years. Following the anomaly detection approach, we propose a new weighted support vector clustering algorithm and apply it to the anomaly detection problem. The weight to each input point is defined according to the position of samples in sphere space. The results of experiment demonstrate that the algorithm has excellent capability and applying it in intrusion detection system can be an effective way via using the data sets of KDD cup 99.
Pricing Model of  Small-Medium Enterprise Mutual Guarantee Bonds with Unexpected Defaults

In many countries, small and medium-sized enterprises (SMEs) are the principal generators of new jobs and economic activity. If guarantee funds are to be effective, a majority of firms can obtain financial assistance through corporate bonds market. This paper describes the mutual guarantee bond which can be a viable solution to the problem of access to credit from capital market for small and middle-entrepreneurs. This work uses a jump diffusion process to estimate the price of mutual guarantee bonds made under the terms of the China Small Business Financing Program. First, a logistic structural model of mutual guarantee bond is built up. The model was then employed to design the logical pricing model of credit spread when an exogenous default process jumps for the first time. A geometrical attenuation function is introduced to reflect the unexpected default of intensities. Furthermore, the pricing model of collective small-medium corporate bonds as the spot interest rate is assumed to follow Vasicek model. Finally, the work tests the pricing model with one thousand times Monte Carlo methods and offer theoretical background and empirical evidence for further financial innovation as well.