Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug Efflux Transporter Multidrug Resistance-Associated Protein 5 Affects Sensitivity of Pancreatic Cancer Cell Lines to the Nucleoside Anticancer Drug 5-Fluorouracil

Pancreatic adenocarcinoma is one of the malignancies that is highly resistant to therapy and among the leading causes of cancer-related death. Several factors may influence pancreatic cancer resistance, and expression of ATP-binding cassette transport proteins is one of the major mechanisms of drug resistance. Members of this family's C-branch, also referred to as multidrug resistance-associated proteins (MRPs), might be of particular interest because they are able to efflux nucleoside analogs used in the treatment of pancreatic cancer. Expression of MRP1, MRP3, MRP4, and MRP5 in human pancreas and pancreatic carcinoma has been reported. However, contributions of MRPs to chemoresistance of pancreatic cancer are not fully understood. MRP5 mRNA expression in pancreatic adenocarcinoma cell lines correlated significantly with cellular sensitivity to 5-fluorouracil (5-FU) (r = 0.738, p < 0.05). Long-term treatment with 5-FU increased expression of MRP5 by 2.4-fold and was associated with significant drug resistance [IC50 values for control and 5-fluorouracil (5-FU)-resistant Patu-T cell lines were 11.3 ± 5.3 and 33.2 ± 6.9 μM, respectively (p < 0.05)]. Consequently, overexpression of MRP5 in Colo-357 cells resulted in significantly reduced accumulation of 5-FU related radioactivity and 5-FU cytotoxicity. Knockdown of MRP5 significantly increased cellular cytotoxicity of 5-FU to Patu-02 cells and enhanced accumulation of radioactivity related to 5-FU and its metabolites. Our results suggest that MRP5 is expressed and functionally active and contributes to variable sensitivities of pancreatic adenocarcinoma cell lines to 5-FU. Further investigations using models that resemble human pancreas tumors are necessary to prove a causative relation between expression and activity of MRP5 and tumor resistance to 5-FU.
Managing Quality of Crowdsourced Data

The Web is the central medium for discovering knowledge via various sources such as blogs, social media, and wikis. It facilitates access to contents provided by a large number of users, regardless of their geographical locations or cultural backgrounds. Such user-generated content is often referred to as crowdsourced data, which provides informational benefit in terms of variety and scale. Yet, the quality of the crowdsourced data is hard to manage, due to the inherent uncertainty and heterogeneity of the Web. In this proposal, we summarize prior work on crowdsourced data that studies quality dimensions and techniques to assess data quality. However, they often lack mechanisms to collect data with high quality guarantee and to improve data quality. To overcome such limitations, we propose a research direction that emphasises on (1) guaranteeing the data quality at collection time, and (2) using expert knowledge to improve data quality for the cases where data is already collected.
Inference in Hidden Markov Models with Explicit State Duration Distributions

In this letter, we borrow from the inference techniques developed for unbounded state-cardinality (nonparametric) variants of the HMM and use them to develop a tuning-parameter free, black-box inference procedure for explicit-state-duration hidden Markov models (EDHMM). EDHMMs are HMMs that have latent states consisting of both discrete state-indicator and discrete state-duration random variables. In contrast to the implicit geometric state duration distribution possessed by the standard HMM, EDHMMs allow the direct parameterization and estimation of per-state duration distributions. As most duration distributions are defined over the positive integers, truncation or other approximations are usually required to perform EDHMM inference.
Risk Factors Associated with Ebola and Marburg Viruses Seroprevalence in Blood Donors in the Republic of Congo

Background Ebola and Marburg viruses (family Filoviridae, genera Ebolavirus and Marburgvirus) cause haemorrhagic fevers in humans, often associated with high mortality rates. The presence of antibodies to Ebola virus (EBOV) and Marburg virus (MARV) has been reported in some African countries in individuals without a history of haemorrhagic fever. In this study, we present a MARV and EBOV seroprevalence study conducted amongst blood donors in the Republic of Congo and the analysis of risk factors for contact with EBOV. Methodology and Findings In 2011, we conducted a MARV and EBOV seroprevalence study amongst 809 blood donors recruited in rural (75; 9.3%) and urban (734; 90.7%) areas of the Republic of Congo. Serum titres of IgG antibodies to MARV and EBOV were assessed by indirect double-immunofluorescence microscopy. MARV seroprevalence was 0.5% (4 in 809) without any identified risk factors. Prevalence of IgG to EBOV was 2.5%, peaking at 4% in rural areas and in Pointe Noire. Independent risk factors identified by multivariate analysis were contact with bats and exposure to birds. Conclusions/Significance This MARV and EBOV serological survey performed in the Republic of Congo identifies a probable role for environmental determinants of exposure to EBOV. It highlights the requirement for extending our understanding of the ecological and epidemiological risk of bats (previously identified as a potential ecological reservoir) and birds as vectors of EBOV to humans, and characterising the protection potentially afforded by EBOV-specific antibodies as detected in blood donors.
Matrix Metalloproteinase 1 Is Necessary for the Migration of Human Bone Marrow-Derived Mesenchymal Stem Cells Toward Human Glioma

Human mesenchymal stem cells (MSCs) have increasingly been used as cellular vectors for the delivery of therapeutic genes to tumors. However, the precise mechanism of mobilization remains poorly defined. In this study, MSCs that expressed similar cell surface markers and exhibited multilineage differentiation potentials were isolated from various donors. Interestingly, different MSC isolates displayed differential migration ability toward human glioma cells. We hypothesized that distinct molecular signals may be involved in the varied tumor tropisms exhibited by different MSC isolates. To test this hypothesis, gene expression profiles of tumor‐trophic MSCs were compared with those of non–tumor‐trophic MSCs. Among the various differentially regulated genes, matrix metalloproteinase one (MMP1) gene expression and its protein activities were enhanced by 27‐fold and 21‐fold, respectively, in highly migrating MSCs compared with poorly migrating MSCs. By contrast, there was no change in the transcriptional levels of other MMPs. Functional inactivation of MMP1 abrogated the migratory potential of MSCs toward glioma‐conditioned medium. Conversely, the nonmigratory phenotype of poorly migrating MSC could be rescued in the presence of either recombinant MMP1 or conditioned medium from the highly migrating MSCs. Ectopic expression of MMP1 in these poorly migrating cells also rendered the cells responsive to the signaling cues from the glioma cells in vivo. However, blocking the interaction of MMP1 and its cognate receptor PAR1 effectively diminished the migratory ability of MSCs. Taken together, this study provides, for the first time, supporting evidence that MMP1 is critically involved in the migration capacity of MSCs, acting through the MMP1/PAR1 axis. STEM CELLS 2009;27:1366–1375
Modulation of Electrocortical Brain Activity by Attention in Individuals with and without Tinnitus

Age and hearing-level matched tinnitus and control groups were presented with a 40 Hz AM sound using a carrier frequency of either 5 kHz (in the tinnitus frequency region of the tinnitus subjects) or 500 Hz (below this region). On attended blocks subjects pressed a button after each sound indicating whether a single 40 Hz AM pulse of variable increased amplitude (target, probability 0.67) had or had not occurred. On passive blocks subjects rested and ignored the sounds. The amplitude of the 40 Hz auditory steady-state response (ASSR) localizing to primary auditory cortex (A1) increased with attention in control groups probed at 500 Hz and 5 kHz and in the tinnitus group probed at 500 Hz, but not in the tinnitus group probed at 5 kHz (128 channel EEG). N1 amplitude (this response localizing to nonprimary cortex, A2) increased with attention at both sound frequencies in controls but at neither frequency in tinnitus. We suggest that tinnitus-related neural activity occurring in the 5 kHz but not the 500 Hz region of tonotopic A1 disrupted attentional modulation of the 5 kHz ASSR in tinnitus subjects, while tinnitus-related activity in A1 distributing nontonotopically in A2 impaired modulation of N1 at both sound frequencies.
Racial-ethnic and National Identification among Children in Middle Childhood: What does it mean to be American?

This mixed methods study explores children's emerging sense of American identity during middle childhood. Conducted in a school setting which is committed to celebrating diversity across multiple domains, researchers investigated the extent to which children in middle childhood identify as American, and explored their beliefs and attitudes about Americans. Open-ended responses indicated that children frequently associated Americans with identifiable symbols and emblems, nationality, and particular racial and ethnic groups. In addition, children from diverse socioeconomic and racial and ethnic backgrounds endorsed positive beliefs about Americans. Quantitative analysis revealed that the ways in which children self-identify as American, differs as a function of generational status, indicating that notions of what it means to be American may be different for children from immigrant families, who tend to explicitly separate notions of racial and ethnic identity from their national American identity. Implications and suggestions for future research on American identity are discussed.
Recognising the last record of sequence

We study the best-choice problem for processes which generalise the process of records from Poisson-paced i.i. d. observations. Under the assumption that the observer knows distribution of the process and the horizon, we determine the optimal stopping policy; and for a parametric family of problems also derive an explicit formula for the maximum probability of recognising the last record.
A comparison of feature and pose-based mapping using vision, inertial and GPS on a UAV

This paper presents and compares two different approaches to integrating sensor information from an Inertial Measuring Unit (IMU), Global Positioning System (GPS) receiver and monocular vision camera mounted to a low-flying Unmanned Aerial Vehicle (UAV) for building large-scale 3D terrain reconstructions. Both approaches utilise a statistically optimal bundle adjustment formulation that incorporates Vision, IMU and GPS observations into the map and pose optimisation process. Our first approach employs a novel pose-only formulation that optimises relative camera poses based on vision feature matches between frames, while incorporating IMU and GPS information. Our approach is related to, but differs from existing pose-graph techniques by formulating a set of 1D epipolar constraints for features matched between two camera frames, rather than minimising 4D feature re-projection errors, or marginalising feature states. We compare results of the method to a second approach which estimates both 3D features and poses together, using airborne vision, IMU and GPS data collected in an ecology mapping application. The results demonstrate a reduction in the computational complexity during optimisation for the pose-only approach, while producing equivalent accuracy in the reconstructed 3D terrain map.
Organization Model of Semantic Document Repository and Search Techniques for Studying Information Technology

— Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document’s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user’s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.
Computable General Equilibrium Models: A Literature Review

AbstractApplied general equilibrium models have become popular tools used on ongoingeconomic policy debates. In this paper we discuss at length the most proeminentfeatures of applied general equilibrium models in a comprehensive and non-technicalway, thus accessible to the reader interested in economic policy but with no priorformal exposure to economic modeling. We rationalize the increasing political demandfor such models as policy analysis tools. We argue that applied general equilibriummodels are best equipped to model regional economies.Keywords: Regional Economic Modeling; CGE Models.JEL Codes: R11; C68. This paper was written within the development of a project to develop ﬁAn Instrument of EconomicPolicy Analysis for the Azoresﬂ, –nanced by several institutions, namely, the US Department of Agriculture,the Luso-American Development Foundation and the Regional Government of the Azores. The project wasmanaged by CEEAplA, an FCT supported center of the Universities of the Azores and Madeira.y
Optimisation of Energy Consumption of Soft Real-Time Applications by Workload Prediction

Embedded real-time systems often operate under energy constraints due to a limited battery lifetime. Modern processors provide techniques for dynamic voltage and frequency scaling to reduce energy consumption. However, while the processor possibly operates at a lower clock frequency, the running applications should still meet their deadlines and thus set some limits to the use of scaling techniques. In this paper, we propose auto correlation clustering (ACC) as a technique to predict the workload of single iterations of a periodic soft real-time application. Based on this prediction we adjust the processor performance such that deadlines are exactly met. We compare our technique to the broadly implemented race-to-idle (RTI) and identify situations where ACC can gain higher energy savings than RTI. Additionally, ACC can help saving energy in multithreaded processors where RTI can be applied only with a high overhead if at all.
SIMULATION OF DIRECT TORQUE CONTROLLED PERMANENT MAGNET SYNCHRONOUS MOTOR DRIVE

In this study, the structure and the control methods of permanent magnet synchronous motor (PMSM) are analysed and a simulation is realized using conventional Direct Torque Control (DTC) method. As a result of this analysis, it is observed that the increase of the electromagnetic torque is directly proportional to the increase of the angle between the stator and rotor magnetic flux linkages.
Analysis and transformation with the nuthatch tree-walking library

Nuthatch is a system for traversing, collecting information from, and rewriting trees, based on the idea of tree walking. The main application is software analysis and transformation. Nuthatch traversals are non-recursive by default and independent of the concrete tree representation. We provide an extensible library, Nuthatch/J, for doing tree walking in Java, with adapters for interfacing with popular software transformation tools like Stratego/XT and Rascal. Transformations are described as walks that proceed in programmer-defined steps. Each step can perform actions based on observed properties of current node and walk, and affect state associated with the walk and also rewrite the walked tree. A step ends by walking to a different node in the tree, following the tree branches, and the walk ends by returning to the top.
The flexible ubiquitous monitor project

A method of making a monolithic semiconductor-on-insulator device which includes silicon islands in spaced relation on the surface of an insulating substrate includes the steps of filling the spaces between the islands with a passivating material by first depositing a layer of a semi-insulating material on the surface of the substrate and extending between adjacent islands into contiguous relation with the side surfaces thereof and then depositing a layer of insulating material on the layer of semi-insulating material. The combined thicknesses of the layers of semi-insulating and insulating material is substantially the same as the thickness of the silicon islands so that the resulting device has a substantially planar surface.
Closed superstring emission from rolling tachyon backgrounds

We compute the lowest components of the type-II Ramond-Ramond boundary state for the tachyon profile T(X) = ? eX0/(2)1/2 by direct path integral evaluation. The calculation is made possible by noting that the integrals involved in the requisite disk one-point functions reduce to integrals over the product group manifold U(n) ? U(m). We further note that one-point functions of more general closed string operators in this background can also be related to U(n) ? U(m) group integrals. Using this boundary state, we compute the closed string emission from a decaying unstable Dp-brane of type-II string theory. We also discuss closed string emission from the tachyon profile T(X) = ? cosh (X0/(2)1/2). We find in both cases that the total number of particles produced diverges for p = 0, while the energy radiated into closed string modes diverges for p ? 2, in precise analogy to the bosonic case.
Trust quality measurement models, and value chain monitoring: symposium introduction

In recent years, trust has become one of the most fashionable topics in the social sciences, and public administration is no exception. As is quite often the case for popular topics, the word “trust” is no longer only used in its original meaning as “a bet on the future contingent actions of others” (Sztompka, 1999), but is used in a broad range of meanings and contexts. In public administration research, two major streams of research can be distinguished. One focuses on the extra-organizational dimension and emphasizes attitudes of actors outside the administration toward this administration. Typically, this research studies citizen attitudes toward the public administration and government. The second stream of research focuses on the internal dimension of public and private organizations. The tension between trust and contracts in steering relations is a central topic here (Kramer & Tyler, 1996), as is the broad range of relationships between administrators, managers, frontline staff, politicians, contractors etc.
Computational Models for Social Network Analysis: A Brief Survey

With the exponential growth of online social network services such as Facebook and Twitter, social networks and social medias become more and more important, directly influencing politics, economics, and our daily life. Mining big social networks aims to collect and analyze web-scale social data to reveal patterns of individual and group behaviors. It is an inherently interdisciplinary academic field which emerged from sociology, psychology, statistics, and graph theory. In this article, I briefly survey recent progress on social network mining with an emphasis on understanding the interactions among users in the large dynamic social networks. I will start with some basic knowledge for social network analysis, including methodologies and tools for macro-level, meso-level and microlevel social network analysis. Then I will give an overall roadmap of social network mining. After that, I will describe methodologies for modeling user behavior including state-of-the-art methods for learning user profiles, and introduce recent progress on modeling dynamics of user behaviors using deep learning. Then I will present models and algorithms for quantitative analysis on social interac- tions including homophily and social influence.Finally, I will introduce network structure model including social group formation, and network topology generation. We will introduce recent developed network embedding algorithms for modeling social networks with the embedding techniques. Finally, I will use several concrete examples from Alibaba, the largest online shopping website in the world, and WeChat, the largest social messaging service in China, to explain how online social networks influence our offline world.
Multi-State Based Facial Feature Tracking and Detection

Accurately and robustly tracking facial features must cope with the large variation in appearance across subjects and the combination of rigid and non-rigid motion. We present a work toward a robust system to detect and track facial features including both permanent (e.g. mouth, eye, and brow) and transient (e.g. furrows and wrinkles) facial features in a nearly frontal image sequence. Multi-state facial component models are proposed for tracking and modeling different facial features. Based on these multi-state models, and without any artificial enhancement, we detect and track the facial features, including mouth, eyes, brows, cheeks, and their related wrinkles and facial furrows by combining color, shape, edge and motion information. Given the initial location of the facial features in the first frame, the facial features can be detected or tracked in remainder images automatically. Our system is tested on 500 image sequences from the Pittsburgh-Carnegie Mellon University (Pitt-CMU) Facial Expression Action Unit (AU) Coded Database, which includes image sequences from children and adults of European, African, and Asian ancestry. Accurate tracking results are obtained in 98% of image sequences.
Quasi-entropies for States of a von Neumann Algebra

In a general von Neumann algebra context the relative entropy of two states was defined and investigated by Araki ([3], see also [5]). When <p and w are normal states on a von Neuman algebra M the relative entropy S(<p,<u) is defined by means of the relative modular operator A (cp, co). r-<logJ(p,a00,0> if J(0>)>j(o0. S(<p 9 co) = \. v + oo otherwise. where Q is the representing vector for co in the natural positive cone of the standard form of M and $(•) denotes the support of a functional. We recall that if M is finite dimensional and possesses a faithful trace r then <p (co) has a density p 9 (p^) and we have Due to its importance in thermodynamics the relative entropy functional has been widely studied ([5], [24]). In this paper we generalize the relative entropy functional and discuss its convexity and some other properties. Our quasi-entropy depends on two parameters k^M and a function f: [0, oo)->JJ e This notion is intimately related to Lieb's concavity as Kosaki ([13]) generalized it and the /-divergence of Gsiszar ([8], [9]) in classical information theory. We recapture Lieb's concavity in Kosaki's form