Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Estimation of Prediction Error and Variable Selection in Linear Regression

An important statistical application is the problem of determining an appropriate set of input variables for modelling a response variable. In such an application, candidate models are characterized by which input variables are included in the mean structure. A reasonable approach to gauging the propriety of a candidate model is to define a discrepancy function through the prediction error associated with this model. An optimal set of input variables is then determined by searching for the candidate model that minimizes the prediction error. In this paper, we focus on a Bayesian approach to estimating a discrepancy function based on prediction error in linear regression. It is shown how this approach provides an informative method for quantifying model selection uncertainty.
Phenotypical Analysis of the Lactobacillus rhamnosus GG Fimbrial spaFED Operon: Surface Expression and Functional Characterization of Recombinant SpaFED Pili in Lactococcus lactis

A noticeable genomic feature of many piliated Gram-positive bacterial species is the presence of more than one pilus-encoding operon. Paradigmatically, the gut-adapted Lactobacillus rhamnosus GG strain contains two different fimbrial operons in its genome. However, whereas one of these operons (called spaCBA) is encoding for the functionally mucus-/collagen-binding SpaCBA pilus, for the other operon (called spaFED) any native expression of the SpaFED-called pili is still the subject of some uncertainty. Irrespective of such considerations, we decided it would be of relevance or interest to decipher the gross structure of this pilus type, and as well assess its functional capabilities for cellular adhesion and immunostimulation. For this, and by following the approach we had used previously to explicate the immuno-properties of SpaCBA pili, we constructed nisin-inducible expression clones producing either wild-type or SpaF pilin-deleted surface-assembled L. rhamnosus GG SpaFED pili on Lactococcus lactis cells. Using these piliated lactococcal constructs, we found that the pilin-polymerized architecture of a recombinant-produced SpaFED pilus coincides with sequence-based functional predictions of the related pilins, and in fact is prototypical of those other sortase-dependent pilus-like structures thus far characterized for piliated Gram-positive bacteria. Moreover, we confirmed that among the different pilin subunits encompassing spaFED operon-encoded pili, the SpaF pilin is a main adhesion determinant, and when present in the assembled structure can mediate pilus binding to mucus, certain extracellular matrix proteins, and different gut epithelial cell lines. However, somewhat unexpectedly, when recombinant SpaFED pili are surface-attached, we found that they could not potentiate the existing lactococcal cell-induced immune responses so elicited from intestinal- and immune-related cells, but rather instead, they could dampen them. Accordingly, we have now provided the first phenotypical description of a spaFED pilus operon, and with that furthered the functional understanding of surface piliation for a particular gut-commensalic genre of piliated Gram-positive bacteria.
Approach to local contrast enhancement

In this article a simple and fully automatic approach to local contrast enhancement is presented, maintaining reasonable computational complexity and feasibility of simultaneous calculations on multiple processors. The authors propose an algorithm, which allows to obtain images with artificially increased dynamic range. The resulting images do not contain unnatural artifacts and are close to images perceived by humans. Results of experiments show that the described method offers very good results even for images obtained with a large range of differences in the exposures.
Luminosities and Space Densities of Gamma-Ray Bursts

We use a homogeneous sample of gamma-ray bursts (GRBs) extracted from 5.9 yr of BATSE DISCLA data and a variety of assumed broken power-law luminosity functions to derive GRB luminosities and space densities. Luminosity functions that are narrow or exhibit no density evolution produce expected redshift distributions that are incompatible with the observation of a GRB redshift of 3.4. For q0 = 0.1 and density evolution rising to 10 at z = 1, we find for a variety of slopes of the luminosity function values of the local space density around 0.18 Gpc-3 yr-1 with a range of only 40%. Characteristic 50-300 keV peak luminosities exhibit a range of a factor of 6 around 6 × 1051 ergs s-1, corresponding to a characteristic total luminosity of 1.2 × 1053 ergs in the 10-1000 keV band. For q0 = 0.5, densities are higher and luminosities lower, both by a factor of 2.5. The local emissivity of GRBs is 1.0 × 1052 ergs Gpc-3 yr-1 in the 10-1000 keV band.
Exploring the Interaction Natures in Plutonyl (VI) Complexes with Topological Analyses of Electron Density

The interaction natures between Pu and different ligands in several plutonyl (VI) complexes are investigated by performing topological analyses of electron density. The geometrical structures in both gaseous and aqueous phases are obtained with B3LYP functional, and are generally in agreement with available theoretical and experimental results when combined with all-electron segmented all-electron relativistic contracted (SARC) basis set. The Pu–Oyl bond orders show significant linear dependence on bond length and the charge of oxygen atoms in plutonyl moiety. The closed-shell interactions were identified for Pu-Ligand bonds in most complexes with quantum theory of atoms in molecules (QTAIM) analyses. Meanwhile, we found that some Pu–Ligand bonds, like Pu–OH−, show weak covalent. The interactive nature of Pu–ligand bonds were revealed based on the interaction quantum atom (IQA) energy decomposition approach, and our results indicate that all Pu–Ligand interactions is dominated by the electrostatic attraction interaction as expected. Meanwhile it is also important to note that the quantum mechanical exchange-correlation contributions can not be ignored. By means of the non-covalent interaction (NCI) approach it has been found that some weak and repulsion interactions existed in plutonyl(VI) complexes, which can not be distinguished by QTAIM, can be successfully identified.
IC / 2004 / 67 Survey of Preference Elicitation Methods

As people increasingly rely on interactive decision support systems to choose products and make decisions, building effective interfaces for these systems becomes more and more challenging due to the explosion of on-line information, the initial incomplete user preference and user’s cognitive and emotional limitations of information processing. How to accurately elicit user’s preference thereby becomes the main concern of current decision support systems. This paper is a survey of the typical preference elicitation methods proposed by related research works, starting from the traditional utility function elicitation and analytic hierarchy process methods, to computer aided elicitation approaches which include example critiquing, needs -oriented interaction, comparison matrix, CP-network, preferences clustering & matching and collaborative filtering.
New algorithm for selecting meniscal allografts that best match the size and shape of the damaged meniscus

Procedures used by tissue banks in selecting meniscal allografts that will best restore normal contact pressure at the time of surgical implantation into a recipient's knee should be improved. Our objective was to develop regression equations that use dimensions measured from magnetic resonance (MR) images of the contralateral knee to predict values of important meniscal parameters of the injured knee. Another objective was to incorporate these equations into an algorithm for selecting allografts that best match the size and shape of the damaged meniscus (either medial or lateral). In each of 10 knee specimens, four transverse and six cross‐sectional parameters of the medial and lateral menisci were quantified from measurements obtained using a laser‐based, noncontacting, 3‐D coordinate digitizing system. In each of 10 contralateral knee specimens, six transverse and 24 cross‐sectional (i.e., perpendicular to transverse plane) dimensions were measured for the medial and lateral menisci from MR images of each knee specimen. Simple linear regression equations related these 10 parameters to each of 38 predictor variables determined from magnetic resonance imaging (MRI) dimensions and the best regression equation for each parameter was identified. Requiring only 9 of the 30 dimensions as predictor variables, the best regression equations predicted 8 of 10 and 10 of 10 medial and lateral menisci parameters, respectively, with R2 values >0.500. The algorithm for selecting meniscal allografts involves: collecting an inventory of meniscal allografts and determining the 10 meniscus parameter values for all allografts in the inventory; measuring the dimensions as required from MRI scans of the uninjured knee; using the dimensions as inputs to the regression equations to predict values of meniscal parameters; and selecting the meniscal allograft from the inventory that best matches the predicted values of meniscal parameters. Selecting meniscal allografts using our new algorithm may enable allografts to better meet the clinical objectives of meniscal transplantation, which are to reduce pain in some patients following meniscal resection and to inhibit the degeneration of the articular cartilage. © 2006 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 24:1535–1543, 2006
Tools of the Mind: A Case Study of Implementing the Vygotskian Approach in American Early Childhood and Primary Classrooms. Innodata Monographs 7.

Goal: Use teaching and classroom strategies to develop children's self-­‐regulation/executive function skills to promote effective learning and achievement. Who: Preschool and Kindergarten age children, primarily at-­‐risk children in urban settings. What: Pre-­‐Kindergarten and Kindergarten curriculum, teaching approach and professional development program for teachers. Trains teachers to use continuous dynamic assessment to scaffold learning and individualize instruction. Where: Head Start classrooms, public preschools, classrooms with a majority of non-­‐English speakers, and inclusion and self-­‐contained special education programs. Assumptions Many children come to school lacking the self-­‐ regulation that is necessary for learning and academic success Increasing self-­‐regulation levels will contribute to school success. Implementing Vygotskian approaches to learning and development as realized in the Tools of the Mind curriculum can promote self-­‐regulation in preschool and kindergarten children while promoting academic achievement Process (Mediators) Increase in self-­‐regulation through participation in Tools curriculum provides:-Ongoing opportunities and scaffolding for mature symbolic make-­‐believe play/dramatization-Activities where practicing S-­‐R is the primary focus (physical regulation, intentionality, attention, memory, and reflection)-Academic activities with embedded S-­‐R practice (attention, memory, planning, monitoring and reflecting on learning). -Heightened opportunities for language development-Teachers' skillful scaffolding within the ZPD for learning processes, reflection on learning, and the learning of content-Activities designed to be self-­‐correcting, where children engage in other-­‐ regulation, and practice in a shared, cooperative context-Activities designed to be intrinsically motivating Outcomes Child Achievement, Engagement, and Social Competence Self-­‐regulated learning Focused attention Deliberate memory Evidence of the use of private speech and other cultural tools Positive task orientation Positive peer interactions Growth in literacy and math skills Overview of the Tools of the Mind approach.
Scrub Typhus and Comparisons of Four Main Ethnic Communities in Taiwan in 2004 versus 2008 Using Geographically Weighted Regression

Purpose: On the main island of Taiwan, a higher risk of scrub typhus infection has been reported in endemic clusters in Southeastern Taiwan and in mountainous township areas. However, research on health care problems associated with scrub typhus in Taiwanese ethnic peoples is limited. This study employs spatial analysis of areal data to determine spatial features related to scrub typhus and the four main Taiwanese ethnicities: Hoklo, Hakka, Mainlander, and aboriginal communities, respectively. Methods: We used a GWR spatial method to analyze the local regressed relationships between scrub typhus incidence and ethnic community percentage in 349 townships in Taiwan, and the subsequent spatial regressed resultants and local parameter estimates were compared between two periods of 2004 and 2008 by kappa statistics. Results: In the GWR models, the spatial regressed relationships of scrub typhus incidences and the Hoklo communities showed significant and negative parameter estimates in numerous locations, showing clusters in Southeastern and Southwestern Taiwan, and areas of the central and southern mountainous townships. Both Hakka and Mainlander communities in the mountainous townships showed less-regressed clusters with scrub typhus prevalence. However, clusters of Aboriginal populations were positively correlated with scrub typhus in highly infected mountainous areas and in Southeastern Taiwan. The kappa value results and the comparisons of local parameter estimates in the 349 townships in Taiwan between 2004 and 2008 indicated that the incidence of scrub typhus in the Hoklo communities was substantial, in the Hakka communities was fair, in the Mainlander communities was slight, and in the aboriginal communities was moderate, respectively. Conclusion: The aboriginal communities have been closely associated with higher risks of scrub typhus in the mountainous townships and in the southeastern portion of Taiwan.
A "divide and conquer" technique for implementing wide dynamic range continuous-time filters

This paper presents a technique for implementing analog filters with wide dynamic range and low power dissipation and chip area. The desired dynamic range of the filter is divided into subranges, each covered by a different filtering path optimized specifically for this subrange. This results in small admittance levels for the individual filtering paths and correspondingly small power dissipation and chip area. The system provides undisturbed output during range switching, contrary to conventional automatic gain control (AGC)/filter arrangements that generate disturbances every time the gain of the AGC changes. We also report on a low-noise highly linear CMOS transconductor useful for high-frequency applications. A chip implementing the ideas of this paper was fabricated in a 0.25-/spl mu/m digital CMOS process. The intended application of the filter is channel selection in an 802.11a/Hiperlan2 Wireless Ethernet receiver. The chip dissipates 9 mA, occupies an area of 0.7 mm/sup 2/, and maintains a signal/(noise + IM3 distortion) ratio of at least 33 dB over a 48-dB signal range, with good blocker immunity. This performance represents at least an order of magnitude improvement over existing channel selection filters, even those that do not achieve disturbance-free operation.
Navigation in Real-World Complex Networks through Embedding in Latent Spaces

Small-world experiments in which packages reach addressees unknown to the original sender through a forwarding chain confirm that acquaintance networks have short paths, a property that was later also discovered in many other networks. They further show that people can find these paths by passing the package on to the acquaintance most socially proximate to the target. This has led researchers to conjecture that perhaps also in many other networks some proximity-based algorithm can be used to find short paths, provided that nodes are given appropriate coordinates. Although potential applications are numerous, ranging from decentralized search to recommendation-based trust to disease control, this conjecture has remained largely unverified. In this paper we apply algorithmic methods to embed nodes in some latent space and employ greedy routing to deliver packages. Using these methods we empirically investigate the navigability of five real-world complex networks from diverse contexts and of varying topology. In each network, we deliver a majority of packages in fewer than six hops.
The Politics of Revenue-Raising Tax Reform in Latin America

Increasing tax revenue is imperative for development and good governance in Latin America. Governments throughout the region experienced continued revenue needs in the aftermath of market-oriented tax reforms implemented in the 1980s and early 1990s, yet tax policy outcomes varied widely, across countries, over time and across tax policy areas. This study explains variation in governments' tax reform agendas and the fate of reform proposals in Chile, Argentina, and Bolivia by analyzing the power of business, a key actor in tax politics in highly unequal societies. Many taxes directly or indirectly affect profits, and business associations may defend the interests of upper-income individuals as well as corporations. The classic concepts of structural power and instrumental power elaborate distinct means of business influence. Structural power arises from a perceived threat that a policy will lead to inadequate investment via market signals. Instrumental power entails deliberate political actions. Sources of instrumental power include relationships with decision-makers and resources that help business pressure policymakers more effectively. When either type of power is strong, taxing elites will be difficult, and reforms that policymakers view as desirable may even be eliminated from the agenda. In Chile, strong instrumental power kept significant tax increases off the agenda. Weaker business power in Argentina gave governments more leeway to increase taxation at the cross-sectoral level, although some powerful sectors prevented tax increases with sector-specific impact. Bolivia is a rare case where business's substantial power was challenged by counter-mobilization on tax issues and a radical threat from popular sectors to the existing political and economic system.The analysis is based on 82 tax proposals embedded in 48 reform packages. Cases in which policymakers decided not to propose tax reforms they viewed as important are also examined. Primary data sources include interviews with high-level government and tax agency officials, politicians, and business leaders, as well as congressional records, newspaper articles, tax agency reports, and tax return statistics. This research provides insights on building state extractive capacity, which has received insufficient attention in political science. It also contributes to theory on business politics by specifying mechanisms through which economic elites influence policy in democratic societies, observable sources of their power, and government strategies that can attenuate their influence on taxation.
Spectral prefetcher: An effective mechanism for L2 cache prefetching

Effective data prefetching requires accurate mechanisms to predict embedded patterns in the miss reference behavior. This paper proposes a novel prefetching mechanism, called the spectral prefetcher (SP), that accurately identifies the pattern by dynamically adjusting to its frequency. The proposed mechanism divides the memory address space into tag concentration zones (TCzones) and detects either the pattern of tags (higher order bits) or the pattern of strides (differences between consecutive tags) within each TCzone. The prefetcher dynamically determines whether the pattern of tags or strides will increase the effectiveness of prefetching and switches accordingly. To measure the performance of our scheme, we use a cycle-accurate aggressive out-of-order simulator that models bus occupancy, bus protocol, and limited bandwidth. Our experimental results show performance improvement of 1.59, on average, and at best 2.10 for the memory-intensive benchmarks we studied. Further, we show that SP outperforms the previously proposed scheme, with twice the size of SP, by 39% and a larger L2 cache, with equivalent storage area by 31%.
Efficient Content-based Image Retrieval for Multi-Image Queries

With explosive growth of digital images, content-based image retrieval has been emerged as an active research topic with many opportunities and challenges. Most of the visual search systems focus on the task of finding specific object, but a little attention has been paid for multiple object retrieval. In this paper, we present an efficient framework for processing multi-image queries, where the users can input multiple images with their objects of interest. We first propose a number of methods to encode image representation of queries. This encoded representation can be indexed further to retrieve an initial list of candidates. Moreover, we present the measuring scheme using Geometric Verification to estimate the similarity between query and candidate images during re-ranking stage. The experimental results performed on a benchmark dataset show that our approach provides promising performance.
Transferring symbolic knowledge into a RuleNet neural network

This paper investigates the use of symbolic knowledge to initialize a RuleNet neural network learning process. The basic idea is to provide the symbolic knowledge induced by either ID3 or NGE to the RuleNet learning process, as the initial knowledge available. The paper describes experiments conducted using seven knowledge domains and focuses the discussion on the accuracy of the induced concepts. The results show that the collaboration is feasible but not necessarily improves the results obtained by RuleNet on its own
Efficient Resource Allocation for MIMO-OFDM Cognitive Networks with Adaptive Precoding

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) combined with cognitive radio is a promising technology for future networks. In this paper, we study the resource allocation in MIMO-OFDM based cognitive radio cellular networks with capacity-achieving adaptive precoding (capacity-achieving in the sense that it approaches the capacity upper-bound of the CR link when the primary radio link is in idle state). Since the formulated optimization task defines a mixed integer programming problem of exponential complexity, we propose a two-phase method to produce an optimal yet efficient solution. Particularly, by jointly considering the signal-tonoise ratios (SNRs) of MIMO-OFDM subcarriers and the interference power introduced to primary users (PUs), we propose an efficient subcarrier allocation procedure and an adaptive precoding selection strategy. Furthermore, we develop a rapid, stable and efficient algorithm to optimally distribute the power among the subcarriers using convex optimization. Numerical results show that our proposal can outperform other standard techniques with respect to the sum-rate and the reduction in complexity.
Synthesis of Fluorophore-Tagged Xylosides That Prime Glycosaminoglycan Chains

Biosynthesis and functions of glycosaminoglycan (GAG) chains are complex and remain elusive. To better understand the factors that regulate the biosynthesis and functions, fluorophore-tagged xylosides carrying two different linkages between fluorophore and xylose residue were synthesized and evaluated for their ability to prime GAG chains such as heparan sulfate (HS), chondroitin sulfate (CS), and dermatan sulfate (DS) in various cell lines. These in vitro studies resulted in the identification of fluorophore-tagged xylosides that prime high molecular weight GAG chains. Primed GAG chains carrying a fluorophore group has several advantages for studying the factors that regulate the biosynthesis, analyzing intact fine structures at low detection limits, and setting the stage for studying structure–function relations of GAG chains of cellular origin.