Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving "bag-of-keypoints" image categorisation: Generative Models and PDF-Kernels

In this paper we propose two distinct enhancements to the basic “bag-of-keypoints” image categorisation scheme proposed in [4]. In this approach images are represented as a variable sized set of local image features (keypoints). Thus, we require machine learning tools which can operate on sets of vectors. In [4] this is achieved by representing the set as a histogram over bins found by k-means. We show how this approach can be improved and generalised using Gaussian Mixture Models (GMMs). Alternatively, the set of keypoints can be represented directly as a probability density function, over which a kernel can be defined. This approach is shown to give state of the art categorisation performance.
SciPDFindexer: Distributed Information Retrieval system using MapReduce

Indexing allows converting raw document collection into easily searchable representation. Bigger scale indexing poses some challenges how to distribute indexing computation efficiently on a cluster of nodes. MapReduce framework promises to be an effective tool for parallelizing computation, especially for divide-and-conquer type of problems, such as inverted index construction. We propose SciPDFindexer, distributed information retrieval system for scientific articles in PDF. Information retrieval (IR) of scientific papers is not much researched domain as general IR and differs from general one mainly by structure of documents and the necessity for converting them into indexable representation. In our system, our main focus is distributed indexing scheme using MapReduce. Given large collection of scientific articles in PDF our system parses and extracts metadata from articles, and then indexes extracted content using our proposed scheme. We also parallelized querying by using distributed database HBase for holding indices. We evaluated our indexing scheme by comparing with alternative approaches and showed that our indexing scheme performs equal or better than the compared ones. In the other experiment, we also investigated impact of different MapReduce parameters to indexing performance. Suggested Reviewers: George Fletcher Ph.D. Assistant Professor, Information Systems W&I, Eindhoven University of Technology g.h. l.fletcher@tue.nl Dr. Fletcher is actively researching on the DB, RDF, and parallelism. C. Lee Giles Ph.D. Professor, College of Information Sciences and Technology, Pennsylvania State University giles@psu.edu Dr. Giles directed the CiteSeerX project. Harshawardhan Gadgil Ph.D. Software Design Engineer, Microsoft hsgadgil@gmail.com He has been researched and published papersin parallel and distributed computing. Sangwon Lee Ph.D. Associate Professor, Information and Communication Engineering, Sungkyunkwan University wonlee@ece.skku. ac.kr He has published over over 50 international journal and conference proceedings and one of them is cited 168 times. He could be a good reviewer for papers in DB area. > We propose a distributed information retrieval system for scientific articles in PDF > Our system parses and extracts metadata from articles, and then indexes extracted content using our proposed scheme > We solve the problem of bigger scale indexing and querying by apply parallelism, using MapReduce and HBase > Evaluation results shows that our indexing scheme by comparing with alternative approaches and showed that our indexing scheme performs equal or better than the compared ones Highlights
Early internet traffic recognition based on machine learning methods

The need to quickly and accurately classify Internet traffic for various traffic shaping purposes and security reasons has been growing steadily. This is due to the many new applications that have been taken place in the field of Internet traffic. As conventional port number based and packet payload based methods are no longer adequate, pattern recognition by learning the statistical flow-based features in the training samples to classify the unknown flows has become popular. The applied method should be fast enough to identify the traffic type in real time before the entire flows are finished. This paper proposes a supervised machine learning based method to identify 7 different types of Internet applications. Our proposed system is able to detect the flows application types after observing just a few first packets in each flow in order to run in real time. The overall accuracy of 84.9% was achieved which is a promising result.
Three-dimensional bioprinting of thick vascularized tissues

Significance Current tissue manufacturing methods fail to recapitulate the geometry, complexity, and longevity of human tissues. We report a multimaterial 3D bioprinting method that enables the creation of thick human tissues (>1 cm) replete with an engineered extracellular matrix, embedded vasculature, and multiple cell types. These 3D vascularized tissues can be actively perfused with growth factors for long durations (>6 wk) to promote differentiation of human mesenchymal stem cells toward an osteogenic lineage in situ. The ability to construct and perfuse 3D tissues that integrate parenchyma, stroma, and endothelium is a foundational step toward creating human tissues for ex vivo and in vivo applications. The advancement of tissue and, ultimately, organ engineering requires the ability to pattern human tissues composed of cells, extracellular matrix, and vasculature with controlled microenvironments that can be sustained over prolonged time periods. To date, bioprinting methods have yielded thin tissues that only survive for short durations. To improve their physiological relevance, we report a method for bioprinting 3D cell-laden, vascularized tissues that exceed 1 cm in thickness and can be perfused on chip for long time periods (>6 wk). Specifically, we integrate parenchyma, stroma, and endothelium into a single thick tissue by coprinting multiple inks composed of human mesenchymal stem cells (hMSCs) and human neonatal dermal fibroblasts (hNDFs) within a customized extracellular matrix alongside embedded vasculature, which is subsequently lined with human umbilical vein endothelial cells (HUVECs). These thick vascularized tissues are actively perfused with growth factors to differentiate hMSCs toward an osteogenic lineage in situ. This longitudinal study of emergent biological phenomena in complex microenvironments represents a foundational step in human tissue generation.
3D modeling of wide area outdoor environments by integrating omnidirectional range and color images

This paper describes a method for modeling wide area outdoor environments by integrating omnidirectional range and color images. The proposed method effectively reconstructs the 3D models of outdoor environments by using omnidirectional laser rangefinder and omnidirectional multi-camera system (OMS). In this paper, we also give experimental results of 3D wide area reconstruction using the data acquired at 50 points in our campus.
Contribution of ERP to the decision-making process through knowledge management

This research explores how knowledge management influences the contribution of enterprise resource planning (ERP) to the decision-making process. An immersion experience including a two-month observation and 24 in-depth interviews was conducted in two North African small and medium-sized industries (SMIs) which used the same ERP. The knowledge creation spiral of Nonaka and Konno (1998) has been applied to both of them. Accordingly, one of the SMIs had some good practices of knowledge management while the other lacked any. Results show that the good practices of knowledge management favour a suitable use of ERP, and consequently lead to an undeniable improvement of the decision-making process. However, practices carried out haphazardly cause fruitless use of ERP, therefore hampering any contribution to the decision-making process. The paper suggests a parallelism between ERP, the decision-making process and knowledge management.
Life Quality After Instrumented Lumbar Fusion in the Elderly

Study Design. Retrospective cohort study. Objective. To review the clinical outcome on elderly patients after spinal instrumented fusion. Summary of Background Data. Although lumbar fusion in elderly patients has increased rapidly, there are only few and conflicting results regarding the clinical outcome. Methods. This retrospective review evaluated 195 patients aged 70 to 89 who underwent lumbar spinal fusion. All 195 patients had follow-ups after 6 weeks, 1 year, and 2 years, including clinical evaluation as well as visual analog scale score, Oswestry Disability Index, and Short Form health survey. Results. Elderly patients benefit from spinal fusion. Back and leg pains were initially reduced by >50%, with a slight deterioration over a 2-year period. Pain medication was reduced in 69% of the patients, and 89.7% of the patients were satisfied. Conclusion. Age itself cannot be considered a contraindication.
A new method to standardize CBCT for quantitative evaluation of alveolar ridge preservation in the mandible: a case report and review of the literature

Cone-beam computerized tomography (CBCT) is an effective technique for assessment of changes to the alveolar ridge (AR). However, its accuracy and reliability could be improved by standardization of imaging positions to remain unchanged during measurements. In this study, an alveolar ridge preservation procedure was performed on a left third molar (38) socket by filling it with a radiotransparent synthetic bone graft, mineralized collagen (MC). Photographic, X-ray and CBCT images were captured before and 3, 6 and 12 months after surgery. A new method was developed to standardize CBCT for quantitative evaluation. Obtained CBCT images showed good comparability. The post-extraction alveolar width and height were both over 95% of the original values, but some resorption of the lingual bone wall (>50%) and inter-crestal bone (>30%). It is concluded that an effective positional standardization method was developed for CBCT assessment of AR dimensional changes in the posterior mandible. The use of MC in combination with a collagen membrane improved dimensional preservation of the AR.
Blood Oxygenation Level-dependent Magnetic Resonance Imaging of Breast Cancer: Correlation with Carbonic Anhydrase IX and Vascular Endothelial Growth Factor

Background: Blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) is a functional MRI technique which involves using the paramagnetic properties of deoxyhemoglobin to image the local tissue oxygen concentration. The purpose of this study was to investigate whether BOLD-MRI could evaluate hypoxia and angiogenesis of breast invasive ductal carcinoma (IDC). Methods: Ninety-eight female patients with IDC were retrospectively included in this research. All patients underwent breast BOLD-MRI at 3.0 T before surgery. R2* values of BOLD-MRI were measured. The expression of carbonic anhydrase IX (CA IX) and vascular endothelial growth factor (VEGF) was analyzed by immunohistochemistry. Spearman's correlation analysis was used to correlate R2* value with CA IX and VEGF levels. Results: Heterogeneous intensity on BOLD-MRI images was the main finding of IDCs. The mean R2* value was 52.8 ± 18.6 Hz. The R2* values in patients with axillary lymph node metastasis were significantly higher than the R2* values in patients without axillary lymph node metastasis (t = 2.882, P = 0.005). R2* values increased with CA IX level and positively correlated with the level of CA IX (r = 0.616, P < 0.001); however, R2* value had no significantly correlation with the level of VEGF (r = 0.110, P = 0.281). Conclusion: BOLD-MRI could noninvasively evaluate chronic hypoxia of IDC, but not angiogenesis.
Artificial Intelligence and Robotics

The recent successes of AI have captured the wildest imagination of both the scientific communities and the general public. Robotics and AI amplify human potentials, increase productivity and are moving from simple reasoning towards human-like cognitive abilities. Current AI technologies are used in a set area of applications, ranging from healthcare, manufacturing, transport, energy, to financial services, banking, advertising, management consulting and government agencies. The global AI market is around 260 billion USD in 2016 and it is estimated to exceed 3 trillion by 2024. To understand the impact of AI, it is important to draw lessons from it's past successes and failures and this white paper provides a comprehensive explanation of the evolution of AI, its current status and future directions.
COMPREHENSIVE TRUST METRICS FOR INFORMATION NETWORKS

Existing computational trust systems analyze information networks to determine the “trustworthiness” of the nodes, but the scalar values they produce are both opaque and semantically variable, and knowing only that the trustworthiness of a website is “27” is not helpful to the user. Moreover, the simplistic means by which they are typically calculated can yield misleading results, sometimes dramatically so. We present a new, standardized set of trust metrics that instead compute the trustworthiness of an information source as a triple of truthfulness, completeness, and bias scores, and argue that these must be calculated relative to the user to be meaningful. We then explore these new metrics with a user study.
Participatory Sensing Meets Opportunistic Sharing: Automatic Phone-to-Phone Communication in Vehicles

This paper explores direct phone-to-phone communication (via WiFi interface) among vehicles to support participatory sensing applications. Sensing data usually contains location, speed, and fuel consumption of the car, and has a long time delay between collected and transferred to the server. Direct communication among phones aboard is important in reducing data transfer delay time and sharing participatory sensing information in an inexpensive manner. We design a practical and optimized communication mechanism for direct phone-to-phone data transfer among phones aboard that strategically enables phone-to-phone and/or phone-to-WiFiAP communications by optimally toggling the phones between the normal client and the hotspot modes. We take advantage of the WiFi hotspot functionality on smartphones, and hence require neither involvement of participants nor changes to existing wireless infrastructure and protocols. An analytical model is established to optimize toggling between client and hotspot modes for optimal system efficiency. We fully implement this system on off-the-shelf Google Galaxy Nexus and Nexus S phones. Through a 35-vehicle two-month deployment study, as well as simulation experiments using the real-world T-drive 9,211-taxicab dataset, we show that our solution significantly reduces data transfer delay time and maintains over 80 percent system efficiency under varying system parameters.
Limiting Exit Location Distributions in the Stochastic Exit Problem

Consider a two-dimensional continuous-time dynamical system, with an attracting fixed point S. If the deterministic dynamics are perturbed by white noise (random perturbations) of strength $\epsilon$, the system state will eventually leave the domain of attraction $\Omega$ of S. We analyze the case when, as $\epsilon\to0$, the exit location on the boundary $\partial\Omega$ is increasingly concentrated near a saddle point H of the deterministic dynamics. We show using formal methods that the asymptotic form of the exit location distribution on $\partial\Omega$ is generically non-Gaussian and asymmetric, and classify the possible limiting distributions. A key role is played by a parameter $\mu$, equal to the ratio $|\lambda_s(H)|/\lambda_u(H)$ of the stable and unstable eigenvalues of the linearized deterministic flow at H. If $\mu < 1$, then the exit location distribution is generically asymptotic as $\epsilon\to0$ to a Weibull distribution with shape parameter $2/\mu$, on the ${\cal O}(\epsilon^{\mu/2})$ .
Intracellular localization of the M1 muscarinic acetylcholine receptor through clathrin-dependent constitutive internalization is mediated by a C-terminal tryptophan-based motif

ABSTRACT The M1 muscarinic acetylcholine receptor (M1-mAChR, encoded by CHRM1) is a G-protein-coupled membrane receptor that is activated by extracellular cholinergic stimuli. Recent investigations have revealed the intracellular localization of M1-mAChR. In this study, we observed constitutive internalization of M1-mAChR in mouse neuroblastoma N1E-115 cells without agonist stimulation. Constitutive internalization depended on dynamin, clathrin and the adaptor protein-2 (AP-2) complex. A WxxI motif in the M1-mAChR C-terminus is essential for its constitutive internalization, given that replacement of W442 or I445 with alanine residues abolished constitutive internalization. This WxxI motif resembles Yxx&PHgr;, which is the canonical binding motif for the &mgr;2 subunit of the AP-2 complex. The M1-mAChR C-terminal WxxI motif interacted with AP-2 &mgr;2. W442A and I445A mutants of the M1-mAChR C-terminal sequence lost AP-2-&mgr;2-binding activity, whereas the W442Y mutant bound more effectively than wild type. Consistent with these results, W442A and I445A M1-mAChR mutants selectively localized to the cell surface. By contrast, the W442Y receptor mutant was found only at intracellular sites. Our data indicate that the cellular distribution of M1-mAChR is governed by the C-terminal tryptophan-based motif, which mediates constitutive internalization.
Leveraging Metadata in NoSQL Storage Systems

NoSQL systems have grown in popularity for storing big data because these systems offer high availability, i.e., operations with high throughput and low latency. However, metadata in these systems are handled today in ad-hoc ways. We present Wasef, a system that treats metadata in a NoSQL database system, as first-class citizens. Metadata may include information such as: operational history for a database table (e.g., columns), placement information for ranges of keys, and operational logs for data items (key-value pairs). Wasef allows the NoSQL system to store and query this metadata efficiently. We integrate Wasef into Apache Cassandra, one of the most popular key-value stores. We then implement three important use cases in Cassandra: dropping columns in a flexible manner, verifying data durability during migrational operations such as node decommissioning, and maintaining data provenance. Our experimental evaluation uses AWS EC2 instances and YCSB workloads. Our results show that Wasef: i) scales well with the size of the data and the metadata; ii) minimally affects throughput and operation latencies.
Bayesian ensemble methods for survival prediction in gene expression data

MOTIVATION We propose a Bayesian ensemble method for survival prediction in high-dimensional gene expression data. We specify a fully Bayesian hierarchical approach based on an ensemble 'sum-of-trees' model and illustrate our method using three popular survival models. Our non-parametric method incorporates both additive and interaction effects between genes, which results in high predictive accuracy compared with other methods. In addition, our method provides model-free variable selection of important prognostic markers based on controlling the false discovery rates; thus providing a unified procedure to select relevant genes and predict survivor functions. RESULTS We assess the performance of our method several simulated and real microarray datasets. We show that our method selects genes potentially related to the development of the disease as well as yields predictive performance that is very competitive to many other existing methods. AVAILABILITY http://works.bepress. com/veera/1/.
Qualität der Wikipedia - Eine vergleichende Studie

Prinzip und Erfolg der Wikipedia sind in mancherlei Hinsicht bemerkenswert. Zunächst fällt vermutlich der rein quantitative Aspekt ins Auge: Die englische Wikipedia [Wikipedia 2007] hat mittlerweile (Stand 6.1.2007) mehr als 1.5 Millionen Artikel, weitere 11 in anderen Sprachen verfasste Wikipedias verfügen über mehr als einhunderttausend Beiträge. Beeindruckend ist auch das Wachstum der Wikipedias, das exponentielle Wachstumsphasen einschließt [Voss 2005, S. 27 ff. ]. Der eigentliche Grund für die Aufmerksamkeit, welche die Wikipedia genießt, liegt jedoch in dem augenscheinlichen Konflikt zwischen dem Anspruch der Wikipedia, enzyklopädisches Wissen ohne Einschränkung in Qualität und Reichweite bereitzustellen, auf der einen Seite und dem Prinzip,
Hormone regulation of the rodent Harderian gland: binding properties of the androgen receptor in the male golden hamster.

Studies were conducted in castrated golden hamsters to assess whether sexual dimorphism and sensitivity to sex steroid hormones in the rodent Harderian gland are mediated by an interaction of androgens with specific intracellular receptors. Physical properties, binding kinetics and stereospecificity of the androgen receptor were analysed using [3H]mibolerone as the radioligand. The presence of [3H]mibolerone-androgen receptor complexes with a sedimentation coefficient of 7-8S was demonstrated in Harderian gland cytosol by a linear sucrose gradient ultracentrifugation technique using a vertical rotor. Kinetic analysis revealed an androgen-binding site with an apparent dissociation constant of 0.3 +/- 0.07 (S.D.) nmol/l and a saturation binding capacity of 113 +/- 15 fmol/mg protein. Displacement studies indicated that unlabelled mibolerone, methyltrienolone, 5 alpha-dihydrotestosterone and testosterone were efficient competitors for the androgen-binding sites, while progesterone, 17 beta-oestradiol, dexamethasone, dehydroepiandrosterone, ethiocholanolone and 5 alpha-16-androsten-3-one were not. Experiments in longterm castrated animals revealed that the Harderian gland androgen receptor concentration and sedimentation coefficient remained unmodified. The results of these studies were interpreted as demonstrating the presence of a specific high-affinity intracellular androgen receptor in the male hamster Harderian gland.
The South Tibetan Detachment System: history, advances, definition and future directions

Abstract Recognition and subsequent study of the syn-convergent low-angle normal faults and shear zones – the South Tibetan Detachment System (STDS) – that form the upper boundary of the Himalayan mid-crust fundamentally changed views of how the Himalayan orogenic system developed. This paper reviews the past four decades of discovery and major advances in our understanding of the detachment system. Significantly conflicting maps of the fault trace, as well as proposed extensions of the detachment system up to hundreds of kilometres both up and down dip of the main fault trace, call for a unifying definition of the detachment system based on structural criteria. The different proposed models for the formation of the STDS during tectonic evolution of the Himalayan orogen are compared. Finally, critical outstanding questions about the origin, extent and character of the detachment system are identified and point to future directions for research.
Combining Text Mining Techniques for QA4MRE 2013

This paper describes a lexical system developed for the main task of Question Answering for Machine Reading Evaluation 2013 (QA4MRE). The presented system executes the preprocessing of test documents, and generates hypotheses consisting of the question text combined with text from possible answers for the question. The hypotheses are compared to sentences from the text by the means of a set similarity measure. The k best similarity scores obtained by each hypothesis are averaged as ranking score for the hypothesis. Two variations of the developed system were utilized, one of them employing coreference detection and resolu- tion techniques in order to take advantage of the discourse structure on the question answering process. The results generated by the systems in QA4MRE 2013 edition are presented and analyzed. The presented system should serve as a solid base for the development of a semantic approach on the task.