Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Global Localization Approach Based on Structural Unit Encoding and Multiple Hypothesis Tracking

In this paper, we present a novel 2-D laser-based global localization approach for mobile robots, which is composed of geometrical relationship construction, a new structural unit encoding scheme (SUES), and an extended multiple hypothesis tracking (MHT) algorithm. Different from existing methods, we construct a 3-D “directional endpoint” feature encapsulating both the endpoint and the direction of a line segment; on this basis, a novel and efficient online structural unit encoding scheme (SUES) is proposed to describe the geometric relationship between the two directional endpoint features with some robustness to dynamic disturbances. Note that SUES presented in this paper is different from the bag-of-words scheme in two aspects: 1) SUES quantizes the geometrical relationship without offline training for vocabulary and 2) SUES is independent of the quality of the vocabulary. By factoring the global localization problem into a discrete pose estimation problem, the MHT is extended on the basis of SUES and odometry information to gradually restore the global robot pose. Different from the classical MHT framework, the extended MHT takes the independent observation results as the a priori, while the likelihood term is composed of consecutive candidate poses and the odometry information. Evaluations are carried out by using both publicly available data sets and self-recorded data sets. Comparative experimental results with respect to the adaptive Monte Carlo localization are presented to show the superior performance of the proposed approach in terms of success ratio and efficiency.
Brief Definitive Report

Phorbol myristate acetate [12-O-tetradecanoyl-phorbol-13-acetate(PMA)] is one of several biologically active substances derived from croton oil, which potentiate the action of a carcinogen in inducing epidermoid tumors of mouse skin (cf. reference 1 for review). Interest in the role of immune response in epidermal carcinogenesis prompted us to investigate possible effects of PMA on lymphocytes. We observed that PMA is a potent mitegen for human peripheral blood lymphocytes (2), an observation confirmed by several laboratories (3-6). In this report, we present evidence that PMA approximates phytohemagglutinin (PHA) in its mitogenic potency, yet acts selectively on a T-lymphocyte subpepulation that has high affinity for sheep erythrocytes (SRBC) and is distinct from that responsive to PHA.
Preliminary results of a prospective randomized study comparing radical prostatectomy versus radical prostatectomy associated with neoadjuvant hormonal combination therapy in T2-3 N0 M0 prostatic carcinoma. The European Study Group on Neoadjuvant Treatment of Prostate Cancer.

OBJECTIVES To evaluate the short- and long-term effects of neoadjuvant hormonal treatment in locally confined prostate cancer. METHODS We report the preliminary results of 354 patients (199 with a clinical T2 tumor and 155 with a clinical T3 tumor) of whom 164 randomly received neoadjuvant total androgen deprivation using a luteinizing-hormone-releasing hormone (LHRH) analog (goserelin) plus flutamide for a period of 3 months. RESULTS Serum prostate-specific antigen (PSA) levels and prostatic volume decreased from a mean of 19.9 ng/mL and 37.7 cm3 to a mean of 0.8 ng/mL and 26.5 cm3 after 3 months of neoadjuvant therapy. "Clinical down-staging" was seen in 32% in the neoadjuvantly treated group. "Pathological downstaging" percentages were 6% and 16% in the direct radical prostatectomy group and neoadjuvantly-treated group, respectively (P < 0.01). In patients with clinical T2 tumors, a significant difference in number of positive margins was shown in favor of the neoadjuvantly treated group (P < 0.01). In patients with clinical T3 tumors, a significant difference could not be detected (P = 0.14). In 215 patients with a mean follow-up time of 15 months, the calculated 95% confidence intervals of mean time of PSA progression-free survival were 26 to 35 months in the neoadjuvantly-treated group and 28 to 37 months in the direct radical prostatectomy group, indicating no significant differences between treatment groups. However, follow-up time is currently too short to draw definite conclusions. CONCLUSIONS These early data confirm high understaging percentages in clinical staging. The clinical relevance of the statistically significant smaller numbers of patients with positive margins in the neoadjuvantly treated group with a clinical T2 tumor will have to be confirmed when further follow-up allows an accurate evaluation of time to PSA progression, local recurrence, and distant metastases. Presently, neoadjuvant therapy is not advisable outside clinical research settings.
Adeno-Associated Viral Vector Serotype 5 Poorly Transduces Liver in Rat Models

Preclinical studies in mice and non-human primates showed that AAV serotype 5 provides efficient liver transduction and as such seems a promising vector for liver directed gene therapy. An advantage of AAV5 compared to serotype 8 already shown to provide efficient correction in a phase 1 trial in patients suffering from hemophilia B, is its lower seroprevalence in the general population. Our goal is liver directed gene therapy for Crigler-Najjar syndrome type I, inherited severe unconjugated hyperbilirubinemia caused by UGT1A1 deficiency. In a relevant animal model, the Gunn rat, we compared the efficacy of AAV 5 and 8 to that of AAV1 previously shown to be effective. Ferrying a construct driving hepatocyte specific expression of UGT1A1, both AAV8 and AAV1 provided an efficient correction of hyperbilirubinemia. In contrast to these two and to other animal models AAV5 failed to provide any correction. To clarify whether this unexpected finding was due to the rat model used or due to a problem with AAV5, the efficacy of this serotype was compared in a mouse and two additional rat strains. Administration of an AAV5 vector expressing luciferase under the control of a liver specific promoter confirmed that this serotype poorly performed in rat liver, rendering it not suitable for proof of concept studies in this species.
An exact algorithm for the maximum quasi-clique problem

Given a graph G = ( V , E ) and a threshold γ ∈ ( 0 , 1], the maximum quasi-clique problem amounts to ﬁnding a maximum cardinality subset C ∗ of the vertices in V such that the edge density of the graph induced in G by C ∗ is greater than or equal to the threshold. This problem is NP-hard and has a number of applications in data mining, for example, in social networks or phone call graphs. In this work, we present an exact algorithm to solve this problem, based on a quasi-hereditary property. We also propose a new upper bound that is used for pruning the search tree. Numerical results show that the new approach is competitive and outperforms the best integer programming approaches in the literature. The new upper bound is consistently tighter than previously existing bounds.
Editorial Preface : Knowledge Management Systems

Welcome to the second issue of the International Journal of Knowledge Management. This issue presents an invited article from David Schwartz that continues the discussion on KM as a discipline. Also included is a review of the AMCIS KM track (continuing our reviews of the major KM conferences). Finally, four research articles are presented that explore the measurement of KM and knowledge management systems (KMSs), in particular KM and KMS success and effectiveness.
Classifying Urban Land Covers Using Local Indices of Spatial Complexity

The skewed statistical distributions of land cover types in complex, heterogeneous urban areas limits the effectiveness of traditional spectrally based maximum-likelihood classifiers. This work examines the utility of fractal dimension and Moran's I index of spatial autocorrelation in segmenting high-resolution panchromatic and lower-resolution multispectral imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze multi-temporal and multi-platform imagery of Atlanta, Georgia. In this example, land cover change trajectories from forest or grassland to built up land covers lead to decreased spatial autocorrelation. In lower resolution imagery such as Landsat MSS, the complex details of forested land covers and urbanized areas are smoothed, and texture-based change detection is less effective. Although segmentation of panchromatic images is possible using fractal dimension or Moran's I, widely differing land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification.
Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board , Washington , D . C . Confidence Intervals for Long-Horizon Predictive Regressions via Reverse Regressions

Long-horizon predictive regressions in finance pose formidable econometric problems when estimated using the sample sizes that are typically available. A remedy that has been proposed by Hodrick (1992) is to run a reverse regression in which short-horizon returns are projected onto a long-run mean of some predictor. By covariance stationarity, the slope coefficient is zero in the reverse regression if and only if it is zero in the original regression, but testing the hypothesis in the reverse regression avoids small sample problems. Unfortunately this only allows the null of no predictability to be tested. In this paper, we show how to use the reverse regression to test other hypotheses about the slope coefficient in a long-horizon predictive regression, and hence to form confidence intervals for this coefficient. We show that this approach to inference works well in small samples, even when the predictors are highly persistent JEL Classification: C12, G12, G17
Title Wirelessly Powered Backscatter Communication Networks : Modeling , Coverage , and Capacity

Future Internet-of-Things (IoT) will connect billions of small computing devices embedded in the environment and support their device-to-device (D2D) communication. Powering these massive number of embedded devices is a key challenge of designing IoT since batteries increase the devices’ form factors and battery recharging/replacement is difficult. To tackle this challenge, we propose a novel network architecture that enables D2D communication between passive nodes by integrating wireless power transfer and backscatter communication, which is called a wirelessly powered backscatter communication (WP-BackCom) network. In this network, standalone power beacons (PBs) are deployed for wirelessly powering nodes by beaming unmodulated carrier signals to targeted nodes. Provisioned with a backscatter antenna, a node transmits data to an intended receiver by modulating and reflecting a fraction of a carrier signal. Such transmission by backscatter consumes orders-of-magnitude less power than a traditional radio. Thereby, the dense deployment of low-complexity PBs with high transmission power can power a large-scale IoT. In this paper, a WP-BackCom network is modeled as a random Poisson cluster process in the horizontal plane where PBs are Poisson distributed and active ad-hoc pairs of backscatter communication nodes with fixed separation distances form random clusters centered at PBs. The backscatter nodes can harvest energy from and backscatter carrier signals transmitted by PBs. Furthermore, the transmission power of each node depends on the distance from the associated PB. Applying stochastic geometry, the network coverage probability and transmission capacity are derived and optimized as functions of backscatter parameters, including backscatter duty cycle, reflection coefficient, and the PB density. The effects of the parameters on network performance are characterized.
Topographic normalization of landsat thematic mapper digital imagery

A two-stage technique is described for the removal of the topographic effect from Landsat Thematic Mapper digital image data. The topographic effect is caused by differential solar illumination of the Earth's surface in undulating terrain. This effect often results in widely varying spectral responses from what are perceived as uniform cover types, which can confound image processing operations such as supervised classification, cluster analysis, and scene segmentation. The process described in this paper, which requires the use of a digital elevation model registered to Landsat TM image data, reduces most of this topographic effect and enables the generation of images with more uniform multispectral response properties. Normalization of Landsat TM radiance data reduced variance, introduced by the topographic effect, by as much as 69 percent. Reduction of the topographic effect in satellite digital multispectral data will improve the overall computer-assisted mapping process.
Observation et modélisation spatiale de pratiques agricoles territorialisées à partir de données de télédétection : application au paysage bocager

Aujourd’hui l’environnement connait des bouleversements fondamentaux dus en grande partie a l’action de l’homme sur les milieux. En effet, tandis que les phenomenes climatiques et biophysiques ont ete pendant longtemps les moteurs principaux des transformations des surfaces terrestres, l’Homme est aujourd’hui a l’origine de la majeure partie des transformations qui affectent les ecosystemes terrestres. Ainsi, les pratiques des acteurs du territoire jouent un role fondamental sur les modifications de l’usage des sols, et par consequent sur les ecosystemes environnementaux. L’intensification de l’agriculture entraine une degradation des milieux « naturels », et de profonds changements dans les structures paysageres. Dans les regions bocageres, la gestion du reseau de haies joue un role determinant dans la conservation des ecosystemes, de la biodiversite tant faunistique que floristique et egalement sur la qualite de l’eau, des sols, … Cette these, centree sur les haies bocageres, porte plus particulierement sur l’identification de pratiques agricoles territorialisees et sur leur organisation spatio‐temporelle. Les objectifs poursuivis dans cette these sont d’etudier les pratiques agricoles effectuees sur les haies en Bretagne a travers leurs interactions avec les structures paysageres, et d’en modeliser le fonctionnement, afin de comprendre comment elles influencent la dynamique du paysage.L‘identification et la caracterisation des pratiques agricoles ont ete effectuees a partir de l’evaluation de differents types d’images de teledetection a haute et tres haute resolution spatiale et de donnees laser aeroportees LiDAR, en utilisant une approche de classification contextuelle orientee‐objets. La modelisation des pratiques agricoles a ete realisee avec un modele multi‐agents, afin de prendre en compte la dimension spatiale des jeux d’acteurs pour evaluer l’influence des pratiques agricoles sur l’evolution du reseau de haies. Les resultats de l’observation du reseau bocager a partir des donnees de teledetection mettent en avant leur complementarite : la caracterisation de la continuite des haies a un niveau fin est rendue possible grâce aux images a tres haute resolution spatiale, tandis que la determination et la cartographie des pratiques agricoles a l’echelle de l’arbre peut etre apprehendee a partir de donnees laser aeroportees de type LiDAR. L’observation et la caracterisation du reseau de haies ont permis de determiner l’arrangement spatial des structures boisees en prenant en compte non plus seulement la presence des elements mais egalement leur emprise dans le paysage et leur agencement au sein de la dynamique temporelle des successions culturales. Le modele multi‐agents developpe a permis d’analyser l’influence des pratiques agricoles sur la dynamique du paysage, et de determiner l’importance de decisions prises au niveau local sur l’evolution du reseau de haies a une echelle superieure
Imaye Restoration Usinr a Hybrid Fourier-Wavelet Domain Hidden Markov Model

We propose an efficient hybrid Fourier-Wavelet domain hidden Markov model. Fourier regularized deconvolution algorithm performs noise regularization using scalar shrinkage in the Fourier domain. The Fourier shrinkage exploit the Fourier transform's economical representation of the colored noise inherent in deconvolution, whereas the hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet coefficients of real-world data. The simplified model specifies the HMT parameters; and makes the model suitable for real-world applications.
The Acceptance of Object-Oriented Development Methodologies in Australian Organizations and the Place of UML in Information Systems Programs

It is claimed that the Unified Modeling Language (UML) is emerging as the accepted standard graphical language for specifying, constructing, visualizing and documenting the object oriented information systems development process. As such it has gained a place in many information systems programs. An investigation of Australian organizations indicates that the use of object oriented development methodologies and UML is gradually increasing in Australia but is still to see general acceptance. This raises the question of the priority that should be accorded to the inclusion of UML in competition with other topics and issues in information systems education programs.
The Theory and Practice of Concurrency

From the Publisher: Since the introduction of Hoares' Communicating Sequential Processes notation, powerful new tools have transformed CSP into a practical way of describing industrial-sized problems. This book gives you the fundamental grasp of CSP concepts you'll need to take advantage of those tools.Part I provides a detailed foundation for working with CSP, using as little mathematics as possible. It introduces the ideas behind operational, denotational and algebraic models of CSP. Parts II and III go into greater detail about theory and practice. Topics include: parallel operators, hiding and renaming, piping and enslavement, buffers and communication, termination and sequencing, and semantic theory. Three detailed practical case studies are also presented.For anyone interested in modeling sequential processes.
Classification of synthetic aperture radar images using Markov Random Field and textural features

Synthetic aperture radar (SAR) is an active imagery system which allows day-and-night and all-weather acquisitions. SAR images are usually affected by a multiplicative noise depending on the ground reflectivity due to the coherence of the radar wavelength [1]. For this reason, classification of SAR images is not a straightforward task, and pixel based classification algorithms will struggle to achieve decent results. a possible solution to this problem is utilizing the spatial relationship between neighboring pixels. The Statistical dependency between neighboring pixels is modeled by Markov Random Field (MRF). In this paper, we present a novel classification algorithm for SAR images using MRF model. The method is based on an iterative expectation maximization (EM) procedure. The iterative process can be initialized by a texture grade images. In this way we avoid all manual intervention. In addition, we suggest an improvement for an existing classification algorithm [2] by using our EM procedure and texture images for expanding the MRF model to a 3-D model. The algorithm estimates the probability density function (PDF) of each class by a pre-defined, dictionary based, stochastic expectation maximization (SEM) procedure [3].
Adaptive query processing: dealing with incomplete and uncertain statistics

The standard Database Management Systems (DBMS) query processing model picks a single non-adaptive plan and executes it to completion. The chosen plan aims to minimize running time by carefully optimizing the use of secondary storage, memory, and CPU. DBMS optimizers estimate plan costs by using statistics---information describing the datasets, the queries, and the system. When statistics needed to cost plans are not available in the database catalog, the optimizer estimates them by using heuristics, by assuming that some data distributions are uniform or independent, and by using a combination of other possibly estimated statistics or default values. These estimates may contain errors and these errors grow exponentially with the number of estimated statistics derived from other estimated statistics. This may lead to selecting a query plan that is sub-optimal by several orders of magnitude. Having more information in the catalog (e.g., histograms) reduces the problem but does not scale with the number of relations and attributes in the database. In addition, several hardware and software trends are making this hard problem harder. For example, the optimization space is increasing exponentially because there are more operators to consider, larger datasets to manage, and more complex queries to optimize. Thus, optimizers are increasingly more likely to select sub-optimal plans. In the general case, DBMS optimizers may have insufficient information to choose a single, good, non-adaptive query plan. Instead of focusing on providing more information to the optimizer, we propose several Adaptive Query Processing (AQP) techniques as alternatives or extensions to the non-adaptive architecture employed by today's commercial database systems. Our proposals are targeted to: (i) correct or avoid query processing problems due to the use of incorrect and partial information at optimization time and (ii) collect information not available at optimization time and dynamically determine and assign different plans for different subsets of the data. The work presented here complements, extends, or supersedes previous AQP proposals.
On the Real Effects of Bank Bailouts: Micro-Evidence from Japan

Exploiting the Japanese banking crisis as a laboratory, we provide firm-level evidence on the real effects of bank bailouts. Government recapitalizations result in positive abnormal returns for the clients of recapitalized banks. After recapitalizations, banks extend larger loans to their clients and some firms increase investment, but do not create more jobs than comparable firms. Most importantly, recapitalizations allow banks to extend larger loans to low and high quality firms alike, and low quality firms experience higher abnormal returns than other firms. Interestingly, recapitalizations by private investors have similar effects. Moreover, bank mergers engineered to enhance bank stability appear to hurt the borrowers of the sounder banks involved in the mergers.
Pay for Performance? CEO Compensation and Acquirer Returns in BHCs

We examine how managerial incentives affect acquisition decisions in the banking industry. We find that higher pay-for-performance sensitivity (PPS) leads to value-enhancing acquisitions. Banks whose CEOs have higher PPS have significantly better abnormal stock returns around the time of the acquisition announcements. On average, acquirers in the high-PPS group outperform their counterparts in the low-PPS group by 1.4% in a three-day window around the announcement. Higher PPS helps reduce the incentives for making value-destroying acquisitions, while at the same time promotes value-enhancing acquisitions. The positive market reaction can be rationalized by post-merger performance. Following acquisitions, banks with higher PPS experience greater improvements in their operating performance. We show that the effect of PPS is mainly evident in small and medium-sized banks, but is not present in large banks. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org. , Oxford University Press.