Miracle-dz/UniFAR-FTUs huggingface dataset:
Base Station Cooperation in MIMO-Aided Multi-User Multi-Cell Systems Employing Distributed Probabilistic Data Association Based Soft Reception

Inter-cell co-channel interference (CCI) mitigation is investigated in the context of cellular systems relying on dense frequency reuse. A distributed Base Station (BS) cooperation aided soft reception scheme using the Probabilistic Data Association (PDA) algorithm and Soft Combining (SC) is proposed for the uplink of multi-user multi-cell MIMO systems. The realistic hexagonal cellular model relying on unity Frequency Reuse (FR) is considered, where both the BSs and the Mobile Stations (MSs) are equipped with multiple antennas. Local cooperation based message passing is used instead of a global message passing chain for the sake of reducing the backhaul traffic. The PDA algorithm is employed as a low complexity solution for producing soft information, which facilitates the employment of SC at the individual BSs in order to generate the final soft decision metric. Our simulations and analysis demonstrate that despite its low additional complexity and backhaul traffic, the proposed distributed PDA-aided reception scheme significantly outperforms the conventional non-cooperative benchmarkers.
Compilation and evaluation of gas-phase diffusion coefficients of reactive trace gases in the atmosphere: volume 2. Organic compounds and Knudsen numbers for gas uptake calculations

The manuscript compiles and discusses diffusion coefficients for organic trace gases, important in atmospheric chemistry. The compiled experimental data are compared to an estimation method by Fuller (in Reid et al. 1987). Based on both, preferred values are suggested. Details of the assessment are documented in IUPAC style in an extensive supplement. This all is excellent work and should be published in ACP. (I did not check the supplement for errors and typos.)
Probabilistic Curve Evolution Using Particle Filters

A probabilistic active contour model is formulated, in which curve evolution is viewed as state estimation for a nonlinear dynamical system. The method is implemented using particle filters in a Bayesian framework. Level set methods are utilized and enable the proposed model to handle topological changes. Experimental results show that the proposed method works well for complicated images, but is, as expected, computationally intense.
Predominance of dense low-density lipoprotein particles predicts angiographic benefit of therapy in the Stanford Coronary Risk Intervention Project.

BACKGROUND LDL particles differ in size and density. Individuals with LDL profiles that peak in relatively small, dense particles have been reported to be at increased risk of coronary artery disease. We hypothesized that response to coronary disease therapy in such individuals might differ from response in individuals whose profiles peak in larger, more buoyant LDL. We examined this hypothesis in the Stanford Coronary Risk Intervention Project, an angiographic trial that compared multifactorial risk-reduction intervention with the usual care of physicians. METHODS AND RESULTS For 213 men, a bimodal frequency distribution of peak LDL density (g/mL) determined by analytical ultracentrifugation was used to classify baseline LDL profiles as "buoyant mode" (density < or = 1.0378) or "dense mode" (density > 1.0378). Coronary disease progression after 4 years was assessed by rates of change (mm/y, negative when arteries narrow) of minimum artery diameter. Rates for buoyant-mode subjects were -0.038 +/- 0.007 (mean +/- SEM) in usual care (n = 65) and -0.039 +/- 0.010 in intervention (n = 56; P = .6). Rates for dense-mode subjects were -0.054 +/- 0.012 in usual care (n = 51) and -0.008 +/- 0.009 in intervention (n = 41, P = .007). Lipid changes did not account for this difference in angiographic response. CONCLUSIONS Different types of LDL profile may predict different-responses to specific therapies, perhaps because metabolic processes determine both LDL profiles and responses to therapies.
UALR at TREC-ENT 2007

Expert search task was to identify experts or subject matter experts given a particular topic. The goal was to drive queries regarding a certain subject be diverted to a particular set of experts. Identifying experts from the document collection is a challenging problem. We have to assert if the document is informative enough for the given topic and shows the mark of an expert. We have to also find the author of the article or the relevant name or email address mentioned. The results were to be submitted as email addresses with proof of documents that we believe are expert information for the given topic. Fifty new topics were provided by NIST 2 and evaluation for expert search task was conducted with help from real-world CSIRO personnel. The document search task was to identify documents that are authoritative information about a given topic. Fifty topics were common among the document search and expert search tasks. The challenge was to determine if the document merely contained words associated with the given topic or the document was indeed the authoritative source on that topic. We had to analyze the documents relevant to the given topic and rank them according to how informative those documents are for that particular topic. We experimented with various approaches that can estimate authoritative information content contained within a document. We discuss these approaches and compare them later in this paper.
The Difference between an Analytical Framework and a Theoretical Claim: A Reply to Martin Carstensen

Martin Carstensen's recent article is a novel attempt to contribute a theory of incremental ideational change to the relevant discourse and institutionalist literatures. Noticing a potentially problematic twin focus on stable ideas and punctuated equilibrium, Carstensen outlines an alternative framework capable of capturing the true dynamism of political ideas. However, his article and analysis are based on the problematic assumption that analytical frameworks, such as historical institutionalism, make theoretical claims about politics, when instead their purpose is to create an underpinning prism for the construction of explanations. By ignoring this important yet subtle distinction, I claim, Carstensen creates a set of criteria for adjudicating the value of analytical frameworks that is both unfair and potentially inappropriate.
Functional Partitioning of Yeast Co-Expression Networks after Genome Duplication

Several species of yeast, including the baker's yeast Saccharomyces cerevisiae, underwent a genome duplication roughly 100 million years ago. We analyze genetic networks whose members were involved in this duplication. Many networks show detectable redundancy and strong asymmetry in their interactions. For networks of co-expressed genes, we find evidence for network partitioning whereby the paralogs appear to have formed two relatively independent subnetworks from the ancestral network. We simulate the degeneration of networks after duplication and find that a model wherein the rate of interaction loss depends on the “neighborliness” of the interacting genes produces networks with parameters similar to those seen in the real partitioned networks. We propose that the rationalization of network structure through the loss of pair-wise gene interactions after genome duplication provides a mechanism for the creation of semi-independent daughter networks through the division of ancestral functions between these daughter networks.
CI-Rank: Ranking Keyword Search Results Based on Collective Importance

Keyword search over databases, popularized by keyword search in WWW, allows ordinary users to access database information without the knowledge of structured query languages and database schemas. Most of the previous studies in this area use IR-style ranking, which fail to consider the importance of the query answers. In this paper, we propose CI-RANK, a new approach for keyword search in databases, which considers the importance of individual nodes in a query answer and the cohesiveness of the result structure in a balanced way. CI-RANK is built upon a carefully designed model call Random Walk with Message Passing that helps capture the relationships between different nodes in the query answer. We develop a branch and bound algorithm to support the efficient generation of top-k query answers. Indexing methods are also introduced to further speed up the run-time processing of queries. Extensive experiments conducted on two real data sets with a real user query log confirm the effectiveness and efficiency of CI-RANK.
Perceptually aberrant experiences as a risk factor for psychosis :: the importance of conditions and explanatory style.

High-risk methodologies in psychopathology research seek to identify groups of individuals at elevated risk for a given psychological disorder as a way to understand the course of illness and potential crucial etiologic factors involved. One approach is to define risk based on the premorbid characteristics of those uho ultimately develop that disorder. Loren Chapman and his associates believe that the presence of body-image distortions and other perceptual disturbances can serve as a premorbid indicator of psychosis, and may be predictive of future psychotic decompensation. They have devised a true-false scale (the Perceptual Aberration scale) to measure the number and variety of these perceptual aberrations, and have observed that high scorers on this scale exhibit a number of characteristics associated with psychotically disturbed populations. But within these risk samples reside an unknown proportion of false positives. The present study had two primary goals. Pirst, we sought a more thorough description of the experience of body-image and other perceptual aberrations, and developed the Perceptual Aberration Interview (PABI) to obtain this description. Second, we hypothesized that the additional information supplied by the PABI might assist in selecting more accurately a population of individuals at-risk for psychosis .
Identifying Beliefs and Cognitions Underpinning Commuters' Travel Mode Choices

Interventions to reduce car use have shown limited success, in part due to limitations in models of transport choices. The theory of planned behavior (TPB) has provided a useful predictive model of car use but the specific beliefs that underpin TPB-specified cognitions are less well understood. In this study, 229 university employees responded to a questionnaire and then reported their commuting choices 1 week later. Intention and perceived behavioral control (PBC) predicted car use (R2 = .79). Intention was predicted by attitude, subjective norm, PBC, and moral norm (R2 = .56). Beliefs could not be differentiated into attitudinal and PBC constructs, but seven beliefs predicted TPB cognitions. A similar model was tested for public transport use. The results identify key targets for future interventions.
Non-destructive techniques for quality control of PV modules: Infrared thermography, electro- and photoluminescence imaging

For a complete quality control of PV cells and modules, a combination of fast and non-destructive methods was investigated. Camera-based measurements, such as electroluminescence (EL), photoluminescence (PL), and infrared (IR) technologies offer excellent possibilities for determining production failures or defects in solar cells and modules, which cannot be detected by means of standard power measurements. The work presented in this paper focuses on quality control and characterization using EL, PL and IR imaging with conventional cameras and an alternative excitation source for the PL-setup.
A Statistical Vector-based Routing Protocol for Wireless Sensor Networks

Establishing stable point-to-point multi-hop routing in Wireless Sensor Networks (WSNs) is challenging because of the dynamics inherent in wireless links. Routing protocols based on virtual coordinates often restrict their routing decisions to connections with a very high and stable quality to avoid the overhead induced by frequent retransmissions and coordinate changes. A link estimator is used to identify stable links based on their quality calculated over a longer time period. However, this approach makes traditional routing protocols miss out on potential opportunities to reduce the hop count and the number of transmissions in the network provided by long range intermediate links. In this thesis we present Statistical Vector Routing (SVR), a protocol that efficiently deals with communication link dynamics in wireless sensor networks. It assigns coordinates based on the statistical distribution of a node’s hop distance to a set of beacon nodes. The routing metric predicts the current location of a node in its address distribution. Our evaluation of a prototype implementation over real testbeds compares SVR with a state-of-the-art virtual coordinates-based routing protocol, i.e. Beacon Vector Routing (BVR). The results indicate that SVR reduces the hop distance towards the beacons by 15% and achieves three times more stable addressing when compared to BVR.
Authenticity in the Adult ESOL Classroom and Beyond

The debate over authenticity is a longstanding one in the teaching of English to speakers of other languages. This article revisits that debate in the context of linguistic-minority adults who, in the process of migration, experience a loss of independence and cultural capital (Bourdieu, 1986/2004). Adult migrants must develop authentic voices in their new second language both for social and interpersonal encounters and in bureaucratic and institutional settings such as job interviews and medical consultations. These needs are not adequately met by invented or oversimplified functional materials which flatten out interactional complexity. Rather, materials should be research based so that they exemplify the social relations and discourse routines of everyday and institutional interactions.
Relación entre autovaloración de consumo de internet y puntuación de adicción a internet en una muestra universitaria / Relationship between consumer self-assessment of internet and scoring of addiction to the internet in a university sample

Con la generalizacion del acceso a internet se han observado algunos casos de un uso desmedido del mismo. En general, la realizacion de cualquier actividad de forma excesiva puede derivar en una adiccion, afectando gravemente a la vida cotidiana de las personas. El objetivo de esta investigacion es analizar la relacion entre el nivel de riesgo estimado por el test de Young, con la autopercepcion de inferencia del uso de Internet en la vida cotidiana en una muestra universitaria. Participaron 323 alumnos de la titulacion de Pedagogia dela Universidad de Malaga (Espana). Se analizo la correlacion entre la puntuacion del alumnado en el test con la contestacion que dieron a dos items sobre autopercepcion de interferencia del uso de internet. Los resultados mostraron una alta relacion entre la autopercepcion y las puntuaciones del test.
Privacy-preserving and Optimal Interval Release for Disease Susceptibility

In this paper, we consider the problem of privacy-preserving release of function outputs that take private information as input. Disease susceptibilities are known to be associated with clinical features (e.g., age, sex) as well as genetic features represented by SNPs of individuals. Releasing outputs are not privacy-preserving if the private input can be uniquely identified by probabilistic inference using the outputs. To release useful outputs with preserving privacy, we present a mechanism that releases an interval as output, instead of an output value. We suppose adversaries perform probabilistic inference using released outputs to sharpen the posterior distribution of the target attributes. Then, our mechanism has two significant properties. First, when our mechanism provides the output, the increase of the adversary's posterior on any input attribute is upper-bounded by a prescribed level. Second, under this privacy constraint, the mechanism can provide the narrowest (optimal) interval that includes the true output. Building such a mechanism is often intractable. We formulate the design of the mechanism as a discrete constraint optimization problem so that it is solvable in a practical computation time. We also propose an algorithm to obtain the optimal mechanism based on dynamic programming. After applying our mechanism to release disease susceptibilities of obesity, we demonstrate that our mechanism performs better than existing methods in terms of privacy and utility.
A New Feature Extraction Method of Intrusion Detection

The paper uses kernel principal component analysis to extract features from the intrusion detection training samples. The method extracts features and reduces the dimensions very effectively. In addition, we make use of RSVM method into nonlinear proximal SVM. It can reduce the computation requirements of the kernel matrix. The combination of the above two methods improve the training speed and classification effect.
Detection of neuronal current MRI in human without BOLD contamination

Controversial results regarding the detectability of neuronal current magnetic resonance imaging (ncMRI) have been reported in different studies on human subjects. In all the previous studies, the ncMRI signal was detected under a continuous and paradigm task‐induced blood oxygen level dependent (BOLD) signal background. The aim of this study is to investigate the possibility of detecting ncMRI signal in human brain in the situation that task‐induced BOLD background is absent or minimum. In this study, by adopting an event‐related visuomotor paradigm with long interstimulus interval (=20 s), the ncMRI signal was detected when the BOLD signal fully returned to its baseline, and the potential BOLD background contamination was avoided effectively. The results showed that the visuomotor stimulation elicited BOLD activation in visual and motor cortices, but no significant ncMRI signal change (in magnitude) was detected in human brain. These experimental findings are consistent with theoretical predications. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.
Comprehensive analysis of gene expression and DNA methylation datasets identify valuable biomarkers for rheumatoid arthritis progression

Rheumatoid arthritis (RA) represents a common systemic autoimmune disease which lays chronic and persistent pain on patients. The purpose of our study is to identify novel RA-related genes and biological processes/pathways. All the datasets of this study, including gene expression and DNA methylation datasets of RA and OA samples, were obtained from the free available database, i.e. Gene Expression Omnibus (GEO). We firstly identified the differentially expressed genes (DEGs) between RA and OA samples through the limma package of R programming software followed by the functional enrichment analysis in the Database for Annotation, Visualization and Integrated Discovery (DAVID) for the exploring of potential involved biological processes/pathways of DEGs. For DNA methylation datasets, we used the IMA package for their normalization and identification of differential methylation genes (DMGs) in RA compared with OA samples. Comprehensive analysis of DEGs and DMGs was also conducted for the identification of valuable RA-related biomarkers. As a result, we obtained 394 DEGs and 363 DMGs in RA samples with the thresholds of |log2fold change|> 1 and p-value < 0.05, and |delta beta|> 0.2 and p-value < 0.05 respectively. Functional analysis of DEGs obtained immune and inflammation associated biological processes/pathways. Besides, several valuable biomarkers of RA, including BCL11B, CCDC88C, FCRLA and APOL6, were identified through the integrated analysis of gene expression and DNA methylation datasets. Our study should be helpful for the development of novel drugs and therapeutic methods for RA.
GLADE: A modern global router considering layer directives

Global routing is a very crucial stage in a design cycle, because it physically plans the routes of nets on a chip. In order to boost the research and development of global routing techniques, ISPD held contests and released benchmarks in 2007 and 2008, respectively. However, the contests may lead researchers away from facing other real problems in practice. In this paper we study a new global routing problem that not only considers traditional routing objectives such as overflow and wirelength but also focuses on honoring layer directives that are usually specified for timing-critical nets to alleviate performance degrading. Based on novel extensions of an academic router, we present a new global router called GLADE for the addressed problem. The experimental results show that GLADE can effectively generate a high-quality solution, which balances the metrics under consideration, for each test case from the set of recently released ICCAD 2009 benchmarks.
The Relationship Between Shame and Acculturation Among Latino/Chicano Students

Abstract Findings are presented from research examining the relationship between shame traits and acculturation status (i.e., Mexican, Anglo, and Bicultural orientations, level/type) of Chicano students (N = 90). Six out of twenty-four shame traits were significantly related to acculturation status; one descriptive-acculturation trait (awareness of ethnic background) lowered shame scores, and place of birth of parents and grandparents affected self-esteem scores. A major consideration in this paper is for educators to evaluate shame and acculturation traits of college students and utilize experiential, adult learning, and strengths-centered approaches to structure teaching in the context of these traits. This study has implications for advancing knowledge on these subjects through replication with diverse student and probability samples.
Network Slicing in Fog Radio Access Networks: Issues and Challenges

Network slicing has been advocated by both academia and industry as a cost-efficient way to enable operators to provide networks on an as-a-service basis and meet the wide range of use cases that the fifth generation wireless network will serve. The existing works on network slicing are mainly targeted at the partition of the core network, and the prospect of network slicing in radio access networks should be jointly exploited. To solve this challenge, enhanced network slicing in F-RANs, called access slicing, is proposed. This article comprehensively presents a novel architecture and related key techniques for access slicing in F-RANs. The proposed hierarchical architecture of access slicing consists of a centralized orchestration layer and a slice instance layer, which makes access slicing adaptively implementable in a convenient way. Meanwhile, key techniques and their corresponding solutions, including radio and cache resource management as well as social-aware slicing, are presented. Open issues in terms of standardization developments and field trials are identified.