Miracle-dz/UniFAR-FTUs huggingface dataset:
Population Stratification in the Context of Diverse Epidemiologic Surveys Sans Genome-Wide Data

Population stratification or confounding by genetic ancestry is a potential cause of false associations in genetic association studies. Estimation of and adjustment for genetic ancestry has become common practice thanks in part to the availability of ancestry informative markers on genome-wide association study (GWAS) arrays. While array data is now widespread, these data are not ubiquitous as several large epidemiologic and clinic-based studies lack genome-wide data. One such large epidemiologic-based study lacking genome-wide data accessible to investigators is the National Health and Nutrition Examination Surveys (NHANES), population-based cross-sectional surveys of Americans linked to demographic, health, and lifestyle data conducted by the Centers for Disease Control and Prevention. DNA samples (n = 14,998) were extracted from biospecimens from consented NHANES participants between 1991–1994 (NHANES III, phase 2) and 1999–2002 and represent three major self-identified racial/ethnic groups: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We as the Epidemiologic Architecture for Genes Linked to Environment study genotyped candidate gene and GWAS-identified index variants in NHANES as part of the larger Population Architecture using Genomics and Epidemiology I study for collaborative genetic association studies. To enable basic quality control such as estimation of genetic ancestry to control for population stratification in NHANES san genome-wide data, we outline here strategies that use limited genetic data to identify the markers optimal for characterizing genetic ancestry. From among 411 and 295 autosomal SNPs available in NHANES III and NHANES 1999–2002, we demonstrate that markers with ancestry information can be identified to estimate global ancestry. Despite limited resolution, global genetic ancestry is highly correlated with self-identified race for the majority of participants, although less so for ethnicity. Overall, the strategies outlined here for a large epidemiologic study can be applied to other datasets accessible for genotype–phenotype studies but are sans genome-wide data.
Divide-and-Conquer Anchoring for Near-Separable Nonnegative Matrix Factorization and Completion in High Dimensions

Nonnegative matrix factorization (NMF) becomes tractable in polynomial time with unique solution under separability assumption, which postulates all the data points are contained in the conical hull of a few anchor data points. Recently developed linear programming and greedy pursuit methods can pick out the anchors from noisy data and results in a near-separable NMF. But their efficiency could be seriously weakened in high dimensions. In this paper, we show that the anchors can be precisely located from low-dimensional geometry of the data points even when their high dimensional features suffer from serious incompleteness. Our framework, entitled divide-and-conquer anchoring (DCA), divides the high-dimensional anchoring problem into a few cheaper sub-problems seeking anchors of data projections in low-dimensional random spaces, which can be solved in parallel by any near-separable NMF, and combines all the detected low-dimensional anchors via a fast hypothesis testing to identify the original anchors. We further develop two non-iterative anchoring algorithms in 1D and 2D spaces for data in convex hull and conical hull, respectively. These two rapid algorithms in the ultra low dimensions suffice to generate a robust and efficient near-separable NMF for high-dimensional or incomplete data via DCA. Compared to existing methods, two vital advantages of DCA are its scalability for big data, and capability of handling incomplete and high-dimensional noisy data. A rigorous analysis proves that DCA is able to find the correct anchors of a rank-k matrix by solving math cal O(klog k) sub-problems. Finally, we show DCA outperforms state-of-the-art methods on various datasets and tasks.
Privacy-Preserving Location Authentication in Wi-Fi Networks Using Fine-Grained Physical Layer Signatures

A recent measurement reveals that a large portion of the reported locations is either forged or superfluous, which raises security issues such as bogus alibis and illegal usage of restricted resources. However, most prior approaches leak users' location information or rely on external devices. To overcome these limitations, we propose PriLA, a privacy-preserving location authentication system that verifies users' location information based on physical layer (PHY) information available in legacy Wi-Fi preambles. The crux of PriLA is to turn detrimental features in wireless systems, namely carrier frequency offset (CFO) and multipath, into useful signatures for privacy protection and authentication. In particular, PriLA exploits CFO and channel state information (CSI) to secure wireless transmissions starting from the handshake phase between mobile users and the access point (AP), and meanwhile verify the truthfulness of users' reported locations based on users' multipath profiles. We have implemented PriLA on GNURadio/USRP platform and commercial off-the-shelf Intel 5300 NICs, and the experimental results show that PriLA achieves the authentication accuracy of 93.2% on average, while leaking merely 45.7% information in comparison with the state-of-the-art approach.
A 3D approach to recommender system evaluation

In this work we describe an approach at multi-objective recommender system evaluation based on a previously introduced 3D benchmarking model. The benchmarking model takes user-centric, business-centric and technical constraints into consideration in order to provide a means of comparison of recommender algorithms in similar scenarios. We present a comparison of three recommendation algorithms deployed in a user study using this 3D model and compare to standard evaluation methods. The proposed approach simplifies benchmarking of recommender systems and allows for simple multi-objective comparisons.
Formulation and Evaluation of Irinotecan Suppository for Rectal Administration

Irinotecan suppository was prepared using the moulding method with a homogeneous blend. A sensitive and specific fluorescence method was developed and validated for the determination of irinotecan in plasma using HPLC. The pharmacokinetics of intravenous administered and rectal administered in rabbits was investigated. Following a single intravenous dose of irinotecan (50 mg/kg), the plasma irinotecan concentration demonstrated a bi-exponential decay, with a rapid decline over 15 min. Cmax, t1/2, AUC0–30h and AUC0-∞ were 16.1 ± 2.7 g/ml, 7.6 ± 1.2 h, 71.3 ± 8.8 μg·h/ml and 82.3 ± 9.5 μg·h/ml, respectively. Following rectal administration of 100 mg/kg irinotecan, the plasma irinotecan concentration reached a peak of 5.3 ± 2.5 μg/ml at 4 h. The AUC0–30h and AUC0-∞ were 32.2 ± 6.2 μg·h/ml and 41.6 ± 7.2 μg·h/ml, respectively. It representing ∼50.6% of the absolute bioavailability.
Data producer catalogs for the web of things: a study on NoSQL solutions

The rise of Web of Things (WoT) has created new challenges for processing distributed data, such as the large volume, heterogeneity and autonomy of data producers. Therefore, efficient mechanisms for publishing and discovering data producers on the WoT become necessary. One possible solution to help such tasks is to provide a catalog with data producers' metadata. That catalog must be flexible, to deal with heterogeneity, and scalable, to deal with massive volume of data producers and consumers. In order to handle those requirements, different NoSQL solutions have been adopted. However, there is still no consensus about the most suitable solution for cataloguing data producers in the context of the WoT. In this work, different NoSQL databases are evaluated and some guidance to help the identification of the most efficient catalog solution for a given workload is also provided.
An empirical investigation into the use of digital photo frames as low cost e-book readers

Tablet computers and e-book readers are growing in popularity, with proponents of the technology citing the device's size, ease of updating content, clarity of the screen (particularly with electronic ink), and ability to store and carry multiple books in a lightweight form. Within the context of education, these devices have begun to be prescribed by schools and universities to replace paper based textbooks. Although tablet computers and e-book readers offer significant advantages over paper-based textbooks, the current cost of the device makes them inaccessible for many users. Digital photo frames on the other hand provide similar functionality to e-book readers, for a fraction of the cost. This paper presents an empirical investigation into the use of digital photo frames as low cost ebook readers in three disadvantaged schools in South Africa. It investigates their use across primary school and high schools, highlighting teachers and learners' enthusiasm about the ability for all learners to be able to see class material without having to print it out. Questionnaires, observations, focus-groups and interviews were all used to solicit participants' perceptions and use of the technology. The data collected was thematically and categorically analysed. Most of the drawbacks emanated from hardware issues experienced by one class in a particular model of digital photo frame. This investigation concluded that digital photo frames could be successfully integrated into the classroom if teachers are provided with adequate training.
Convergence Analysis of Local Algorithms for Blind Decorrelation

In this paper we analyze and extend a class of adaptive networks for second order blind decorrelation of instantaneous signal mix tures Firstly we compare the performance of the decorrelation neural network employing global knowledge of the adaptive co e cients in with a similar structure whose coe cients are adapted via local output connections in Through statistical analyses the convergence behaviors and stability bounds for the algorithms step sizes are studied and derived Secondly we ana lyze the behaviors of locally adaptive multilayer decorrelation net works and quantify their performances for poorly conditioned sig nal mixtures Thirdly we derive a robust locally adaptive network structure based on a posteriori output signals that remains sta ble for any step size value Finally we present an extension of the locally adaptive network for linear phase temporal and spatial whitening of multichannel signals Simulations verify the analy ses and indicate the usefulness of the locally adaptive networks for decorrelating signals in space and time
Low-Distortion Embeddings of Trees

We prove that every tree T=(V, E) on n vertices can be embedded in the plane with distortion \( O(\sqrt n )\) that is, we construct a mapping f: V → R 2 such that \( \rho (u,\upsilon ) \leqslant \parallel f(u) - f(\upsilon )\parallel \leqslant O(\sqrt n ) \cdot \rho (u,\upsilon )\) for every u, υ ∈ V, where ρ(u, υ) denotes the length of the path from u to υ in T (the edges have unit lengths). The embedding is described by a simple and easily computable formula.This is asymptotically optimal in the worst case. We also prove several related results.
Kooperierende Mobile Roboter Cooperating Mobile Robots

Der Einsatz von Teams kooperierender mobiler Roboter ist erforderlich, wenn eineAufgabe inharent verteilt ist oder nicht von einem Roboter allein bew altigt werden kann.Auch wenn Aufgaben prinzipiell von Einzelrobotern erledigt werden konnen, kann derEinsatz mehrerer Roboter Vorteile bringen, da Roboterteams schneller, robuster undskalierbarer sein konnen. Bei der Steuerung kooperierender mobiler Robotern m ussenvielfaltige Ressourcenzuordnungsprobleme gel ost werden, beispielsweise dieAufgabenzuordnung oder die Zuordnung von Gebieten des Arbeitsraums. Im Artikelwerden Kommunikations- und Kontrollarchitekturen, sowie Pfadplanungs- undLernverfahren diskutiert, die fur Multi-Roboter-Systeme entwickelt wurden. Die m oglicheNutzlichkeit kooperierender mobiler Roboter wird durch vier Anwendungsbeispieleillustriert.The use of teams of cooperating mobile robots is necessary, if a task is inherentlydistributed or cannot be solved by a single robot. In cases when a task can in principlebe completed by a single robot, the use of multiple robots can result in advantages inexecution speed, robustness, and scalability. Multiple resource allocation problems mustbe solved to make robots cooperate, like task allocation or the allocation of portions ofthe work space. This article discusses architectures for communication and control inmulti-robot systems as well as path planning and multi-robot learning. The possibleutility of cooperating mobile robots is illustrated using four application examples.Schlagworter: Mobile Roboter, Kooperation, Multi-Agenten-Systeme.Keywords: Mobile robots, cooperation, multi-agent-systems.
Efficient hardware support for the Partitioned Global Address Space

We present a novel architecture of a communication engine for non-coherent distributed shared memory systems. The shared memory is composed by a set of nodes exporting their memory. Remote memory access is possible by forwarding local load or store transactions to remote nodes. No software layers are involved in a remote access, neither on origin or target side: a user level process can directly access remote locations without any kind of software involvement. We have implemented the architecture as an FPGA-based prototype in order to demonstrate the functionality of the complete system. This prototype also allows real world measurements in order to show the performance potential of this architecture, in particular for fine grain memory accesses like they are typically used for synchronization tasks.
In Vitro Effects of Propranolol on T Helper Type 1 Cytokine Profile in Human Leukemic T Cells

Introduction: Cytokines are a large group of proteins play a key role in inflammation. Down-regulation of pro-inflammatory cytokines has beneficial effect on heart function. Propranolol, as a non selective beta-adrenergic blocker, has been extensively used for treatment of many cardiovascular problems such as arrhythmias and heart malfunction. In addition anti-inflammatory effects of propranolol have been revealed. In this study the propranolol effect on T helper type 1 cytokine profile in human leukemic T cells has been assessed in vitro. Materials and methods: Human leukemic T cells (Molt-4 and Jurkat) were cultured in complete RPMI medium. The cells were then incubated with different concentrations of propranolol (0.03- 30 µM) in the presence or absence of PHA (10 µg/ml) for 48 hours. The supernatants of cell culture media were collected and used for cytokines assay. Results: Propranolol significantly decreased the T helper type 1 cytokine profile [Interleukin-2 (IL-2) and Interferon- γ (IFN-γ)] production in PHA stimulated Molt-4 and Jurkat cells, after 48 hour of incubation time, dose-dependently compared to untreated control cells. Conclusion: Our data showed a dose dependent inhibitory effect of propranolol on the IL-2 and IFN-γ production in human leukemic Molt-4 and Jurkat cells. The anti- inflammatory effect of propranolol reported by other investigators may be in part due to its suppressive effect on production of inflammatory cytokines such as IL-2 and IFN-γ. So, propranolol along with its chronic long-term usage in cardiovascular problems may have potential implication in treatment of inflammatory-based disorders.
A Survey of XML Tree Patterns

With XML becoming a ubiquitous language for data interoperability purposes in various domains, efficiently querying XML data is a critical issue. This has lead to the design of algebraic frameworks based on tree-shaped patterns akin to the tree-structured data model of XML. Tree patterns are graphic representations of queries over data trees. They are actually matched against an input data tree to answer a query. Since the turn of the 21st century, an astounding research effort has been focusing on tree pattern models and matching optimization (a primordial issue). This paper is a comprehensive survey of these topics, in which we outline and compare the various features of tree patterns. We also review and discuss the two main families of approaches for optimizing tree pattern matching, namely pattern tree minimization and holistic matching. We finally present actual tree pattern-based developments, to provide a global overview of this significant research topic.
Institutional investors, financial market efficiency, and financial stability

Emphasising the scope for further growth in institutional investment, in Europe in particular, this paper focuses on the impact of institutional investment on the efficiency and stability of financial systems. The paper stresses the scope for efficiency gains arising from an increasing role of institutional investors, reflecting - inter alia - their role in improving corporate governance. The paper also argues that institutional investors tend to enhance financial system stability although they may sporadically exacerbate market volatility or liquidity problems. This calls for a close focus of regulators and monetary policy makers on institutional behaviour, while inter alia continuing the shift envisaged in the current EU Pension Funds (IORP) Directive towards a "prudent-person rule" for investment, and focusing closely on the long-term sustainability of guarantees being offered on life policies, annuities and pensions.
X/Ku-Band SiGe BiCMOS Phased Array Chips with Simultaneous 2- and 4-Beam Capabilities

This paper presents RFIC phased array receive chips capable of formation 2and 4simultaneous beams from the same antenna input with 4-bit amplitude and phase control. The design is based on a SiGe BiCMOS process (Jazz SiGe18Hx) and results in excellent isolation between the different beams. The 2beam chip results in a gain of 5-6 dB per channel at 14-15 GHz, a noise figure of 10.0 dB, a P1dB of -13 dBm per channel (IIP3 of -6 dBm), and an RMS phase and gain error of < 12 and 1.5 dB, respectively. A gain control of 17 dB is available at each channel. Most important, the on-chip isolation between the channels has been fully characterized and is > 30 dB at 11-15 GHz. The beams can operate over an instantaneous bandwidth of > 1 GHz at any frequency between 11 and 15 GHz, and both beams can be at the same frequency if required. The 4-beam chip is currently being tested and the results will be reported at the conference. KeywordsSiGe BiCMOS, phased array, phase shifter
TSDPMM: Incorporating Prior Topic Knowledge into Dirichlet Process Mixture Models for Text Clustering

Dirichlet process mixture model (DPMM) has great potential for detecting the underlying structure of data. Extensive studies have applied it for text clustering in terms of topics. However, due to the unsupervised nature, the topic clusters are always less satisfactory. Considering that people often have some prior knowledge about which potential topics should exist in given data, we aim to incorporate such knowledge into the DPMM to improve text clustering. We propose a novel model TSDPMM based on a new seeded P´ olya urn scheme. Experimental results on document clustering across three datasets demonstrate our proposed TSDPMM significantly outperforms stateof-the-art DPMM model and can be applied in a lifelong learning framework.
Exclamations as multi-dimensional intersubjective items

This article is an introduction to the special issue of the Revue de Semantique et Pragmatique on Exclamation and Intersubjectivity. It points out that Exclamations were misleadingly restricted to the ego-area. They are actually involved in dialogs. They are context-sensitive and even include information transmission as one of their felicity conditions. Cross-linguistic data show that they play a particularly important role in situations of negotiation and argumentation.
Targeted Liposomal Drug Delivery to Monocytes and Macrophages

As the role of monocytes and macrophages in a range of diseases is better understood, strategies to target these cell types are of growing importance both scientifically and therapeutically. As particulate carriers, liposomes naturally target cells of the mononuclear phagocytic system (MPS), particularly macrophages. Loading drugs into liposomes can therefore offer an efficient means of drug targeting to MPS cells. Physicochemical properties including size, charge and lipid composition can have a very significant effect on the efficiency with which liposomes target MPS cells. MPS cells express a range of receptors including scavenger receptors, integrins, mannose receptors and Fc-receptors that can be targeted by the addition of ligands to liposome surfaces. These ligands include peptides, antibodies and lectins and have the advantages of increasing target specificity and avoiding the need for cationic lipids to trigger intracellular delivery. The goal for targeting monocytes/macrophages using liposomes includes not only drug delivery but also potentially a role in cell ablation and cell activation for the treatment of conditions including cancer, atherosclerosis, HIV, and chronic inflammation.
Context as autonomic intelligence in a ubiquitous computing environment

This paper presents the ANS architecture that uses ubiquitous computing to monitor medical patients at home. Since there is no notion of the patient carrying out maintenance of such a system, it must be self-managing or autonomic. In the ANS, sensors such as temperature, location, etc., use a form of logic to abduce a context, i.e., the state/quality of a given device or its function. Our contribution lies in the emergent autonomicity of the architecture driven by its ability to derive the most appropriate source for a particular application. This is done by allowing the application to define mathematically its own notion of what level of service provides the best satisfaction and is based on Quality of Context (QoC) attributes that describe each alternative. The ANS framework is lightweight and can provide real-time adaptation, which is necessary in resource-starved ubiquitous computing environments that support medical applications.