Miracle-dz/UniFAR-FTUs huggingface dataset:
Crowdsourcing solution for mobile resource consumption analysis

The outstanding increase in smartphone adoption rates across the globe in recent years has created the opportunity to analyze large amounts of data produced by mobile usage in the search for a means to improve the user experience. Several solutions exist that help the user understand the resource consumption of the mobile device. However, their estimates are rough and hardly accurate. We believe that leveraging crowdsourcing can lead in the future to better insights for the user over the mobile device. In this paper, we describe our current status in designing and implementing a centralized system for aggregation and statistical analysis of resource consumption traces from mobile devices. We evaluate the system using a real-world dataset covering hundreds of devices over three months.
Is there a neuropathology difference between mild cognitive impairment and dementia?

The number of studies that have investigated the neuropathology of mild cognitive impairment (MCI) is small, but growing. In this paper we have restricted our focus to the consideration of the presence and extent of postmortem findings relevant to the neuropathology of Alzheimer's disease. We have drawn from studies that have investigated the postmortem neurobiology of the brains of persons with cognitive function at the interface between unimpaired normal function and mild but definite dementia. The data derived from these studies suggest that i) the brains of persons with MCI evidence significant neuropathological and neurobiological changes relative to those without coqnitive impairment; ii) in general, the neuropathological and neurobiological changes are qualitatively similar to those observed in the brains of persons with frank AD-like dementia; and iii) the neuropathological and neurobiological brain changes associated with MCI are quantitatively less than those of persons who meet criteria for dementia. Thus, the available, albeit limited, data suggests that MCI is associated with the early stages of the neurobiological and neuropathological changes that culminate in the florid lesions of AD; including the accumulation of neuritic plaques, neurofibrillary tangles, synaptic and neurotransmitter associated deficits, and significant neuronal cell death.
OPTICAL CONTROL PLANE FOR GRID NETWORKS

an enabling technology, allowing flexible and adaptable routing for unpredictable network traffic. A working group in the Global Grid Forum (GGF) is currently committed to the standardization of OBS in the context of Grid computing [2]. In this article, it is shown how OBS can enable a Grid platform to be accessible by a massive number of highly dynamic users, a concept denoted as consumer Grids [3]. General characteristics and requirements of the platform are discussed and the architecture, functionality, and interfaces of all relevant entities residing both in the core and at the edge of the network are presented. Furthermore, issues related to the control and management of these Grid networks are discussed, and current initiatives and overall directions for future investigation are presented.
Cytotoxicity of Mononuclear Cells as Induced by Peritoneal Dialysis Fluids: Insight into Mechanisms that Regulate Osmotic Stress-Related Apoptosis

Objective High glucose content of peritoneal dialysis fluids (PDFs) has been shown to contribute to loss of peritoneal function during long-term peritoneal dialysis. However, hyperosmolality and hypertonicity of PDF are usually seen as similar stress events inducing osmotic stress-induced programmed cell death. In this study, we examined the impact of various osmotic agents on apoptosis induced by hyperosmolar PDFs, focusing on the mechanisms underlying the lethal effects of PDFs on peripheral blood mono-nuclear cells (PBMCs). Methods We assessed apoptosis and necrosis by annexin V–propidium iodide (PI) labeling, and caspase-3 activity by fluorescence assay. F-actin remodeling was measured using fluorescent phalloidin labeling. Results Hyperosmolality does not cause the cytotoxicity observed with PDF, but exposure to agents incapable of permeating cell membranes results in a significant increase in the percentage of apoptotic PBMCs by annexin V–PI labeling, which is confirmed by the increase in caspase-3 activity. Interestingly, inhibition of caspase-3 by Z-VAD-FMK did not suppress apoptosis. Extracellular hypertonicity produced polymerization of filamentous actin and cell shrinkage, which displayed similar time courses. Cell shrinkage was blocked by cytochalasin D, indicating an active role for actin cytoskeleton in hypertonicity-induced cell shrinkage. F-actin polymerization was related to an increase in intra-cellular ionic strength. Finally, we excluded a direct role for actin remodeling in osmotic stress-induced programmed cell death. Conclusions Exposure to osmolytes that cannot penetrate cell membranes results in a hypertonicity-induced apoptosis that cannot be blocked by the broad-spectrum caspase inhibitor Z-VAD-FMK. In addition, extracellular hypertonicity induced by impermeant solutes produces F-actin polymerization through an increase in intracellular ionic strength. The remodeling of the cytoskeleton does not modulate apoptosis but participates in cell shrinkage.
Distributed Representations of Expertise

Collaborative networks are common in real life, where domain experts work together to solve tasks issued by customers. How to model the proficiency of experts is critical for us to understand and optimize collaborative networks. Traditional expertise models, such as topic model based methods, cannot capture two aspects of human expertise simultaneously: Specialization (what area an expert is good at? ) and Proficiency Level (to what degree? ). In this paper, we propose new models to overcome this problem. We embed all historical task data in a lower dimension space and learn vector representations of expertise based on both solved and unsolved tasks. Specifically, in our first model, we assume that each expert will only handle tasks whose difficulty level just matches his/her proficiency level, while experts in the second model accept tasks whose levels are equal to or lower than his/her proficiency level. Experiments on real world datasets show that both models outperform topic model based approaches and standard classifiers such as logistic regression and support vector machine in terms of prediction accuracy. The learnt vector representations can be used to compare expertise in a large organization and optimize expert allocation.
Rural Substance Abuse: State of Knowledge and Issues. Proceedings of a meeting. April 26-27, 1994.

ii ACKNOWLEDGMENT This monograph is based on the papers from a technical review on "Rural Substance Abuse: State of Knowledge and Issues" held on April 26-27, 1994. The review meeting was sponsored by the National Institute on Drug Abuse. The National Institute on Drug Abuse has obtained permission from the copyright holders to reproduce certain previously published material as noted in the text. Further reproduction of this copyrighted material is permitted only as part of a reprinting of the entire publication or chapter. For any other use, the copyright holder's permission is required. All other material in this volume except quoted passages from copyrighted sources is in the public domain and may be used or reproduced without permission from the Institute or the authors. Citation of the source is appreciated. Opinions expressed in this volume are those of the authors and do not necessarily reflect the opinions or official policy of the National Institute on Drug Abuse or any other part of the U.S. Department of Health and Human Services. The U.S. Government does not endorse or favor any specific commercial product or company. Trade, proprietary, or company names appearing in this publication are used only because they are considered essential in the context of the studies reported herein. NIDA Research Monographs are indexed in the Index Medicus. They are selectively included in the coverage of American Statistics Index,
Infinite dimensional spherical analysis

Introduction In these notes we present some new developments in asymptotic harmonic analysis due to Vershik, Kerov, Okunkov, and Olshanski. The purpose of this analysis is to study the asymptotics of functions related to harmonic analysis on groups or homogeneous spaces as the dimension goes to infinity. The subject is not new. In 1938 Schoenberg considered the case of infinite dimensional Euclidean spaces. For instance Schoenberg determined the continuous functions Φ on [0, ∞[ such that, for every n, the function Φ x 2 1 + · · · + x 2 n is of positive type on R n. He considered also a similar problem on spheres and Krein on hyperbolic spaces. Olshanski developped a general theory of the inductive limit (G, K) of an increasing sequence (G(n), K(n) of Gelfand pairs, introducing the notion of spherical function for such a pair ([Olshanski, 1990]). Several results about specific infinite dimensional pairs can be stated in this general framework. A natural queston arises: is it possible to obtain the spherical functions for the inductive limit (G, K) as limits of spherical functions for the Gelfand pair G(n), K(n) ? As far I know there is presently no general answer. In these notes we will present results by Olshanski, Ver-shik, Kerov, and Okunkov for certain sequences of Riemannian symmetric spaces as the rank goes to infinity. In the first chapter we present some basic results about Olshanski spherical pairs, from the paper [Olshanski, 1990]. We review in Chapter 2 basic properties of Schur functions and Schur expansions, then introduce the shifted Schur functions, with some of their properties, from the paper [Okunkov-Olshanski,1998a]. In Chapter 3 we consider the space of infinite dimensional Hermitian matrices with the action of the infinite dimensional unitary group, and describe the asymptotics of the orbital integrals. This is mainly a review of the main results in [Olshanski-Vershik,1996]. Chapter 4 deals with asymp-totics of the characters of the unitary group U (n). The main result is from [Vershik-Kerov,1982], but we present the method of proof from [Okunkov-Olshanski,1998b]. We end by a short review of some results about induc-tive limits of compact symmetric spaces from the recent paper [Okunkov-Olshanski,2006]. Further references can be found in [Faraut,2006]. These notes are issued from a series of talks given at the Mathematical Institute of Kyushu University in September 2007. I was visiting Kyushu University in the framework of the COE program. …
Natural Assemblages of Marine Proteobacteria and Members of the Cytophaga-Flavobacter Cluster Consuming Low- and High-Molecular-Weight Dissolved Organic Matter

ABSTRACT We used a method that combines microautoradiography with hybridization of fluorescent rRNA-targeted oligonucleotide probes to whole cells (MICRO-FISH) to test the hypothesis that the relative contributions of various phylogenetic groups to the utilization of dissolved organic matter (DOM) depend solely on their relative abundance in the bacterial community. We found that utilization of even simple low-molecular-weight DOM components by bacteria differed across the major phylogenetic groups and often did not correlate with the relative abundance of these bacterial groups in estuarine and coastal environments. The Cytophaga-Flavobacter cluster was overrepresented in the portion of the assemblage consuming chitin,N-acetylglucosamine, and protein but was generally underrepresented in the assemblage consuming amino acids. The amino acid-consuming assemblage was usually dominated by the α subclass of the class Proteobacteria, although the representation of α-proteobacteria in the protein-consuming assemblages was about that expected from their relative abundance in the entire bacterial community. In our experiments, no phylogenetic group dominated the consumption of all DOM, suggesting that the participation of a diverse assemblage of bacteria is essential for the complete degradation of complex DOM in the oceans. These results also suggest that the role of aerobic heterotrophic bacteria in carbon cycling would be more accurately described by using three groups instead of the single bacterial compartment currently used in biogeochemical models.
Dynamic Data Selection for Neural Machine Translation

Intelligent selection of training data has proven a successful technique to simultaneously increase training efficiency and translation performance for phrase-based machine translation (PBMT). With the recent increase in popularity of neural machine translation (NMT), we explore in this paper to what extent and how NMT can also benefit from data selection. While state-of-the-art data selection (Axelrod et al., 2011) consistently performs well for PBMT, we show that gains are substantially lower for NMT. Next, we introduce ‘dynamic data selection’ for NMT, a method in which we vary the selected subset of training data between different training epochs. Our experiments show that the best results are achieved when applying a technique we call ‘gradual fine-tuning’, with improvements up to +2.6 BLEU over the original data selection approach and up to +3.1 BLEU over a general baseline.
Integration of People Detection and Simultaneous Localization and Mapping Systems for an Autonomous Robotic Platform

This paper presents the implementation of a people detection system for a robotic platform able to perform Simultaneous Localization and Mapping (SLAM), allowing the exploration and navigation of the robot considering people detection interaction. The robotic platform consists of a Pioneer 3DX robot equipped with an RGB-D camera, a Sick Lms200 sensor laser and a computer using the robot operating system ROS. The idea is to integrate the people detection system to the simultaneous localization and mapping (SLAM) system of the robot using ROS. Furthermore, this paper presents an evaluation of two different approaches for the people detection system. The first one uses a manual feature extraction technique, and the other one is based on deep learning methods. The manual feature extraction method in the first approach is based on HOG (Histogram of Oriented Gradients) detectors. The accuracy of the techniques was evaluated using two different libraries. The PCL library (Point Cloud Library) implemented in C ++ and the VLFeat MatLab library with two HOG variants, the original one, and the DPM (Deformable Part Model) variant. The second approaches are based on a Deep Convolutional Neural Network (CNN), and it was implemented using the MatLab MatConvNet library. Tests were made objecting the evaluation of losses and false positives in the people's detection process in both approaches. It allowed us to evaluate the people detection system during the navigation and exploration of the robot, considering the real time interaction of people recognition in a semi-structured environment.
Gene Knockdown by EpCAM Aptamer–siRNA Chimeras Suppresses Epithelial Breast Cancers and Their Tumor-Initiating Cells

Effective therapeutic strategies for in vivo siRNA delivery to knockdown genes in cells outside the liver are needed to harness RNA interference for treating cancer. EpCAM is a tumor-associated antigen highly expressed on common epithelial cancers and their tumor-initiating cells (TIC, also known as cancer stem cells). Here, we show that aptamer–siRNA chimeras (AsiC, an EpCAM aptamer linked to an siRNA sense strand and annealed to the siRNA antisense strand) are selectively taken up and knock down gene expression in EpCAM+ cancer cells in vitro and in human cancer biopsy tissues. PLK1 EpCAM-AsiCs inhibit colony and mammosphere formation (in vitro TIC assays) and tumor initiation by EpCAM+ luminal and basal-A triple-negative breast cancer (TNBC) cell lines, but not EpCAM− mesenchymal basal-B TNBCs, in nude mice. Subcutaneously administered EpCAM-AsiCs concentrate in EpCAM+ Her2+ and TNBC tumors and suppress their growth. Thus, EpCAM-AsiCs provide an attractive approach for treating epithelial cancer. Mol Cancer Ther; 14(10); 2279–91. ©2015 AACR.
Database Proxies for Component-Based Real-Time Systems

We introduce the concept of database proxies capable of mitigating the gap between two disjoint productivity-enhancing techniques: Component Based Software Engineering (CBSE) and Real-Time Database Management Systems (RTDBMS). The coexistence of the two techniques is neither obvious nor intuitive since CBSE and RTDBMS promotes opposing design goals, CBSE promotes encapsulation and decoupling of component internals from the component environment, whilst RTDBMS provide mechanisms for efficient and predictable global data sharing. Database proxies decouple components from an underlying database residing in the component framework. This enables components to remain encapsulated and reusable, while providing temporally predictable access to data maintained in a database. We specifically target embedded systems with a subset of functionality with real-time requirements. Our implementation results show that the above benefits do not come at the expense of run-time overheads or less accurate timing predictions.
A systematic review and meta-analysis of DNA methylation levels and imprinting disorders in children conceived by IVF/ICSI compared with children conceived spontaneously.

The authors would like to apologise for errors in some of the data shown in Figure 3 of this article. These have mainly arisen from lackof conversion of some standard error of the mean (SEM) values to standard deviations (SD) during entry of the data for meta-analysis, inconsistency in incorporating new values communicated by individual authors and genuine clerical errors in data entry and labelling. In the text below we have described the amendments with respect to each of the relevant primary papers included in the meta-analysis. All values have been rechecked and means and SDs have been rounded up to two decimal places. A single post-decimal figure is shown where the value of the second is zero.
Convex and star-shaped sets associated with stable distributions

It is known that each symmetric stable distribution in $R^d$ is related to a norm on $R^d$ that makes $R^d$ embeddable in $L_p([0,1])$. In case of a multivariate Cauchy distribution the unit ball in this norm corresponds is the polar set to a convex set in $R^d$ called a zonoid. This work interprets general stable laws using convex or star-shaped sets and exploits recent advances in convex geometry in order to come up with new probabilistic results for multivariate stable distributions. In particular, it provides expressions for moments of the Euclidean norm of a stable vector, mixed moments and various integrals of the density function. It is shown how to use geometric inequalities in order to bound important parameters of stable laws. It is shown that each symmetric stable laws appears as the limit for the sum of sub-Gaussian laws and an estimate for the probability distance to a sub-Gaussian law is given. Operations with convex sets induce the well-known and new operations with stable vectors. Furthermore, covariation, regression and orthogonality concepts for stable laws acquire geometric interpretations. A similar collection of results is presented for one-sided stable laws.
Low-Complexity Detection of POI Boundaries Using Geo-Tagged Tweets: A Geographic Proximity Based Approach

Users tend to check in and post their statuses in location-based social networks (LBSNs) to describe that their interests are related to a point-of-interest (POI). Since the relevance of the data to the POI varies according to the geographic distance between the POI and the locations where the data are generated, it is important to characterize an area-of-interest (AOI) that enables to utilize the location information in a variety of businesses, services, and place advertisements. While previous studies on discovering AOIs were conducted based mostly on density-based clustering methods with the collection of geo-tagged photos from LBSNs, we focus on detecting a POI boundary, which corresponds to only one cluster containing its POI center. Using geo-tagged tweets recorded from Twitter users, this paper introduces a low-complexity two-phase strategy to detect a POI boundary by finding a suitable radius reachable from the POI center. We detect a polygon-type boundary of the POI as the convex hull (i.e., the outermost region) of selected geo-tags through our two-phase approach, where each phase proceeds on with different sizes of radius increment, thus yielding a more precise boundary. It is shown that our approach outperforms the conventional density-based clustering method in terms of runtime complexity.
Arrangement based image representation for scene recognition

Studies on human faculties of scene recognition have lead to two broad classifications of the perceived information: local and global. It has been shown that both are processed separately and combined towards final category assignment. Recently, it was suggested that accuracy of computational models for local information closely match human performance, while it is not so for current global representations. In this paper, we propose a new global representation, AGIR. The key differences we propose to current approaches is the explicit modeling of `arrangement' (co-occurrence and configuration) in the scene, and use of multiple hierarchical dictionaries. The effectiveness of the proposed scheme is shown through various experiments and comparisons on both indoor and outdoor scene recognition.
International conflict mediation : new approaches and findings

1: New Approaches, Methods, and Findings in the Study of Mediation Jacob Bercovitch and Scott Gartner Part I: Mediation Strategy 2: Is There Method in the Madness of Mediation? Some Lessons for Mediators from Quantitative Studies of Mediation Jacob Bercovitch and Scott Gartner 3: Third-Party Intermediaries and Negotiated Settlements, 1946-2000 Derrick V. Frazier and William J. Dixon Part II: Mediator Type A. Bias and Information 4: Credibility and Strategy in International Mediation Zeev Maoz and Lesley G. Terris 5: Mediator Types and the Effectiveness of Information Provision Strategies Burcu Savun B. UN & Neutrality 6: Guaranteeing Peace: The Credibility of Third-Party Mediators in Civil Wars Isak Svensson 7: Choosing Sides: UN Resolutions and Non-Neutrality Michelle Benson and Nil Satana Part III: Dispute and Crisis Types 8: Softening Up: Making Conflicts More Amenable to Diplomacy J. Michael Greig and Paul F. Diehl 9: Power Play: Mediation in Symmetric and Asymmetric International Crises David Quinn, Jonathan Wilkenfeld, Kathleen Smarick and Victor Asal 10: Protracted Conflict and Crisis Mediation: a Contingency Approach David Carment, Yiagadeesen Samy and Souleima EL Achkar Part IV: The Conflict Management Environment 11: Practicing Democratic Community Norms: Third Party Conflict Management and Successful Settlements Sara McLaughlin Mitchell, Kelly M. Kadera, Mark J.C. Crescenzi 12: Philippine and Taiwanese Legal Mediation James Wall, Tsungting Chung, Daniel Druckman and Wan Yan Part V: Data 13: Conflict and Mediation Event Observations (CAMEO): An Event Data Framework for a Post Cold War World Deborah J. Gerner, Philip A. Schrodt and Omur Yilmaz