Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized multiple-access relay channel with confidential messages

In this paper, we propose information theoretic schemes that achieve the rate-equivocation regions for the multiple-access relay channel with confidential messages. This channel consists of two users that play the role of eavesdropper for each other's message and a relay that helps them to have a reliable and secure communication. The relay can itself be an eavesdropper of the users messages. The first coding scheme used for achievability is noise forwarding strategy and the second is the combination of noise forwarding with the compress and forward strategy. In the first one, relay cooperates with the users to have a confidential communication by sending codewords independent of the secret messages. In the second one, in addition to sending independent codewords, relay also sends compressed version of the received signals. Using these schemes, we derive the inner bounds for the capacity-equivocation region of the described model.
The influence of class order on rule induction results

The basic sequential rule induction algorithm does not define a specific class order. Class order is generally selected based on heuristics. We have implemented the basic rule induction algorithm together with several discretization and evaluation methods and varying class orders. Tests in several basic data sets show that the class order considerably influences the resulting accuracy of sequential rule induction. While the class order sometimes has a higher influence than the tested rule quality measures (FOIL and Likelihood Ratio) and the simple discretization algorithms, there is no single class order that provides best results for all tested combinations of discretization and rule quality measure approaches in all cases.
Noise mitigation over Powerline communication using LDPC-Convolutional Code and fusion of mean and median filters

In this paper, we propose a new impulse noise mitigation approach in Orthogonal Frequency Division Multiplexing (OFDM) signals over Powerline communication (PLC) channel. Recently LDPC-Convolutional Code (LDPC-CC) has received much interest as an alternative to LDPC codes for its advantages and low complexity. The proposed approach exploits the redundancy introduced by LDPC-CC and cyclic prefix (CP) added to the OFDM transmitter to recover noisy coefficients. It is based on the fusion of median and mean of their neighboring coefficients using a window and a dynamic threshold calculated on the basis of noise variance and the peak value of the noise in the received signal. Detection of noisy coefficients takes into consideration the neighboring coefficients. The proposed technique presents a good robustness to impulse noise performance without adding a big complexity to the transmission system. Promising results have been achieved by the proposed approach when compared to filtering and coding techniques alone.
Weakly Supervised Learning of Part-based Models for Interaction Prediction via LDA

In this paper, we focus on interaction prediction which infers to what interaction might happen in the near future. Each interaction is modeled by mixtures of deformable parts in order to provide higher tolerance to part configurations. In our weakly supervised learning setting, part detectors are learned from training data without bounding boxes around the true locations of the people in each frame. The discriminating features are obtained using a two-layer Linear Discriminant Analysis (LDA) classification to promise maximal separability for parts and interactions respectively. Experimental results demonstrate that the proposed system is effective in learning part-based models in less annotated information and achieves comparable performance to state-of-the-art fully supervised approaches.
Frequency estimation and detection for sinusoidal signals with arbitrary envelope: a nonlinear least-squares approach

In this paper, we consider the problem of estimating the frequency of a sinusoidal signal whose amplitude could be either constant or time-varying. We present a nonlinear least-squares (NLS) approach when the envelope is time-varying. We show that the NLS estimator can be efficiently implemented using a FFT. A statistical analysis shows that the NLS frequency estimator is nearly efficient. The problem of detecting amplitude time variations is next addressed. A statistical test is formulated, based on the statistics of the difference between two frequency estimates. The test is computationally efficient and yields as a by-product consistent frequency estimates under either hypothesis (i.e. constant or time-varying amplitude). Numerical examples are included to show the performance in terms of both estimation and detection.
Apolipoprotein E ε4 allele decreases functional connectivity in Alzheimer’s disease as measured by EEG coherence

OBJECTIVES The ε4 allele of apolipoprotein E (APOE) represents a major biological risk factor for late onset Alzheimer’s disease. However, it is still not known whether the APOE genotype affects the progression of the disease, assessed by different functional methods. METHODS The study sample included 41 patients with probable Alzheimer’s disease. Subjects had similar severity of disease, age of onset, and duration of illness, and were subcategorised according to their APOE genotypes: 17 with no ε4 allele, 14 with one ε4 allele, and 10 with two ε4 alleles. The control group consisted of 18 healthy subjects comparable with the patients in age and education. Analysed quantitive EEG (qEEG) variables were the ratio of alpha and theta absolute power and EEG coherence in alpha frequency band, representing major cortical association pathways. RESULTS There was pronounced EEG slowing in all three patient subgroups compared with the controls for the alpha/theta ratio, but there was no significant difference across the patient subgroups. Patients homozygous for the APOE ε4 allele had reduced right and left temporoparietal, right temporofrontal, and left occipitoparietal coherence. Patients without and with one ε4 allele showed an overlap between the control group and group with two ε4 alleles in coherence measures. CONCLUSIONS APOE ε4 does not influence EEG slowing, an index which reflects severity of the disease in patients with Alzheimer’s disease, but seems to be associated with selective decreases in functional connectivity as assessed by EEG coherence. This finding might be of clinical importance when considering different pathogenetic mechanisms.
INFLATION-HEDGING POTENTIAL OF NIGERIAN BREWERY STOCKS

Inflation is an ill-wind that blows no one any good. It is an important variable in investment decision. In inflationary period, investors are usually jittery because not only that their invested capital and expected income are at risk of extinction, the possibility of maintaining the value of the investment to command the expected purchasing power is heavily threatened. To combat this monster called inflation and protect the purchasing power of investment income, the investor should properly examine his potential investment assets to make sure such can offer him the security of his capital and income in real terms. Against this background, this study sets to examine the inflation-hedging potentials of investment in equity stocks of quoted brewers in Nigeria between 2000 and 2011. The study applied real rate of return on equity and regression analysis to find the stocks that provide positive real return and offer inflation-hedging potentials respectively. The findings revealed that in terms of real return based on shareholders’ funds and total return to equity, all the firms were not susceptible to adverse effect of inflation but when based on dividend yield all the firms offered no significant hedge against inflation.
Illustrative Logistic Regression Examples using PROC LOGISTIC: New Features in SAS/STAT ® 9.2

PROC LOGISTIC has many useful features for model selection and the understanding of fitted models. The standard generated output will give valuable insight into important information such as significant variables and odds ratio confidence intervals. However, proper utilization of output files, graphical displays and relevant options can further enhance justification of model choice and understanding of model fit. In this fairly general paper, a variety of logistic regression topics such as model building, model fitting and the ROC curve will be reviewed. The discussion will introduce the “PLOTS=” option, as well as the ROCCONTRAST statement as new features which are available in SAS/STAT ® 9.2.
zflncRNApedia: A Comprehensive Online Resource for Zebrafish Long Non-Coding RNAs

Recent transcriptome annotation using deep sequencing approaches have annotated a large number of long non-coding RNAs in zebrafish, a popular model organism for human diseases. These studies characterized lncRNAs in critical developmental stages as well as adult tissues. Each of the studies has uncovered a distinct set of lncRNAs, with minor overlaps. The availability of the raw RNA-Seq datasets in public domain encompassing critical developmental time-points and adult tissues provides us with a unique opportunity to understand the spatiotemporal expression patterns of lncRNAs. In the present report, we created a catalog of lncRNAs in zebrafish, derived largely from the three annotation sets, as well as manual curation of literature to compile a total of 2,267 lncRNA transcripts in zebrafish. The lncRNAs were further classified based on the genomic context and relationship with protein coding gene neighbors into 4 categories. Analysis revealed a total of 86 intronic, 309 promoter associated, 485 overlapping and 1,386 lincRNAs. We created a comprehensive resource which houses the annotation of lncRNAs as well as associated information including expression levels, promoter epigenetic marks, genomic variants and retroviral insertion mutants. The resource also hosts a genome browser where the datasets could be browsed in the genome context. To the best of our knowledge, this is the first comprehensive resource providing a unified catalog of lncRNAs in zebrafish. The resource is freely available at URL: http://genome.igib. res.in/zflncRNApedia
Assessment of publication bias, selection bias, and unavailable data in meta-analyses using individual participant data: a database survey

Objective To examine the potential for publication bias, data availability bias, and reviewer selection bias in recently published meta-analyses that use individual participant data and to investigate whether authors of such meta-analyses seemed aware of these issues. Design In a database of 383 meta-analyses of individual participant data that were published between 1991 and March 2009, we surveyed the 31 most recent meta-analyses of randomised trials that examined whether an intervention was effective. Identification of relevant articles and data extraction was undertaken by one author and checked by another. Results Only nine (29%) of the 31 meta-analyses included individual participant data from “grey literature” (such as unpublished studies) in their primary meta-analysis, and the potential for publication bias was discussed or investigated in just 10 (32%). Sixteen (52%) of the 31 meta-analyses did not obtain all the individual participant data requested, yet five of these (31%) did not mention this as a potential limitation, and only six (38%) examined how trials without individual participant data might affect the conclusions. In nine (29%) of the meta-analyses reviewer selection bias was a potential issue, as the identification of relevant trials was either not stated or based on a more selective, non-systematic approach. Investigation of four meta-analyses containing data from ≥10 trials revealed one with an asymmetric funnel plot consistent with publication bias, and the inclusion of studies without individual participant data revealed additional heterogeneity between trials. Conclusions Publication, availability, and selection biases are a potential concern for meta-analyses of individual participant data, but many reviewers neglect to examine or discuss them. These issues warn against uncritically viewing any meta-analysis that uses individual participant data as the most reliable. Reviewers should seek individual participant data from all studies identified by a systematic review; include, where possible, aggregate data from any studies lacking individual participant data to consider their potential impact; and investigate funnel plot asymmetry in line with recent guidelines.
Effect of cements on fracture resistance of monolithic zirconia crowns

Abstract Objectives The present study investigated the effect of cements on fracture resistance of monolithic zirconia crowns in relation to their compressive strength. Materials and methods Four different cements were tested: zinc phosphate cement (ZPC), glass-ionomer cement (GIC), self-adhesive resin-based cement (SRC) and resin-based cement (RC). RC was used in both dual cure mode (RC-D) and chemical cure mode (RC-C). First, the compressive strength of each cement was tested according to a standard (ISO 9917-1:2004). Second, load-to-failure test was performed to analyze the crown fracture resistance. CAD/CAM-produced monolithic zirconia crowns with a minimal thickness of 0.5 mm were prepared and cemented to dies with each cement. The crown–die samples were loaded until fracture. Results The compressive strength of SRC, RC-D and RC-C was significantly higher than those of ZPC and GIC (p < 0.05). However, there was no significant difference in the fracture load of the crown between the groups. Conclusion The values achieved in the load-to-failure test suggest that monolithic zirconia crowns with a minimal thickness of 0.5 mm may have good resistance against fracture regardless of types of cements.
Cooperative Intergroup Mating Can Overcome Ethnocentrism in Diverse Populations

Ethnocentrism is a behavioral strategy seen on every scale of social interaction. Game-theory models demonstrate that evolution selects ethnocentrism because it boosts cooperation, which increases reproductive fitness. However, some believe that interethnic unions have the potential to foster universal cooperation and overcome in-group biases in humans. Here, we use agent-based computer simulations to test this hypothesis. Cooperative intergroup mating does lend an advantage to a universal cooperation strategy when the cost/benefit ratio of cooperation is low and local population diversity is high.
Intra-Industry Trade in the Portuguese Economy: Products and Partners

These simultaneous trade flows can be either associated with a specialization along qualityranges (intra-industry trade in vertically differentiated products) or associated with a specialization invarieties (intra-industry trade in similar, horizontally differentiated products). This article analyses the evolution of Portuguese intra-industry trade over the 1995-2004 period, on abilateral basis and with a very detailed product breakdown. The article adopts the methodology pro-posed by Fontagne and Freudenberg (1997), which allows elementary trade flows to be broken downinto three categories accordingto similarityin unit values and trade overlap: inter-industrytrade (insig-nificant overlap between exports and imports); horizontal intra-industry trade (significant overlap andlimiteddifferencesinunitvalues);verticalintra-industrytrade(significantoverlapandlargedifferencesin unit values). The traditionalGrubel-Lloydindexis alsocomputedandthe results of both methodsforthe Portuguese economy are compared.The article is organized as follows. Section 2 discusses the methodologies for the measurement ofintra-industry trade and describes the database. Section 3 examines the evolution of intra-industrytradeinPortugaloverthe1995-2004periodalongtheproductandgeographicaldimensions.Section4presents some concluding remarks.
In silico analyses of substrate interactions with human serum paraoxonase 1

Human paraoxonase (HuPON1) is a serum enzyme that exhibits a broad spectrum of hydrolytic activities, including the hydrolysis of various organophosphates, esters, and recently identified lactone substrates. Despite intensive site‐directed mutagenesis and other biological studies, the structural basis for the specificity of substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The results suggest that the active site of HuPON1 is characterized by two distinct binding regions: the hydrophobic binding site for arylesters/lactones, and the paraoxon binding site for phosphotriesters. The unique binding modes proposed for each type of substrate reveal a number of key residues governing substrate specificity. The polymorphic residue R/Q192 interacts with the leaving group of paraoxon, suggesting it plays an important role in the proper positioning of this substrate in the active site. MD simulations of the optimal binding complexes show that residue Y71 undergoes an “open‐closed” conformational change upon ligand binding, and forms strong interactions with substrates. Further binding free energy calculations and residual decomposition give a more refined molecular view of the energetics and origin of HuPON1/substrate interactions. These studies provide a theoretical model of substrate binding and specificity associated with wild type and mutant forms of HuPON1, which can be applied in the rational design of HuPON1 variants as bioscavengers with enhanced catalytic activity. Proteins 2008. Published 2008 Wiley‐Liss, Inc.
Improving lives by interorganizational collaboration : A collaboration analysis on a social development project

To organize and implement social development projects through interorganizational collaboration is common, but lack empirical studies from a psychological perspective. The study´s aim was to make a collaboration analysis on the implementing actors within a social development project, to understand how the collaboration was functioning. The study took place within a project for marginalized groups in Tanzania, arranged by a Swedish NGO and implemented by interorganizational collaboration. Eight participants were interviewed on six areas: Environment, Membership characteristics, Process and Structure, Communication, Purpose, and Resources. The findings highlight the complexity of interorganizational collaboration. The studied collaborative network is overall working in the same direction, but has both functional and dysfunctional areas where the dysfunctional need to be improved for the collaboration to work well. The study indicates that interorganizational collaboration brings benefits for social development projects, and the six areas studied seem to cover essential areas of interorganizational collaboration.
Temperature-Compensated Force/Pressure Sensor Based on Multi-Walled Carbon Nanotube Epoxy Composites

In this study, we propose a multi-walled carbon nanotube epoxy composite sensor for force and pressure sensing in the range of 50 N–2 kN. A manufacturing procedure, including material preparation and deposition techniques, is proposed. The electrode dimensions and the layer thickness were optimized by the finite element method. Temperature compensation is realized by four nanocomposites elements, where only two elements are exposed to the measurand. In order to investigate the influence of the filler contents, samples with different compositions were prepared and investigated. Additionally, the specimens are characterized by cyclical and stepped force/pressure loads or at defined temperatures. The results show that the choice of the filler content should meet a compromise between sensitivity, temperature influence and noise behavior. At constant temperature, a force of at least 50 N can be resolved. The measurement error due to the temperature influence is 150 N in a temperature range of −20°C−50°C.
Quantum inspired genetic algorithm for energy efficient clustering in wireless sensor networks

Clustering has been one of the most commonly used strategies for maximizing the lifetime of wireless sensor networks (WSNs). Clustering in WSNs is the process of grouping the sensors based on some criteria and optimal clustering in WSNs is known to be a NP-Hard problem. Evolutionary algorithms (e.g. genetic algorithm) have been extensively utilized for addressing this problem. In this paper, energy efficient clustering problem has been dealt with using a relatively new meta-heuristic technique known as quantum inspired genetic algorithm. The simulation results and analysis clearly indicate that the proposed approach outperforms genetic algorithm based clustering technique and leads to significant increase in network lifetime.
Inconclusive Innovation “Returns”: A Meta‐Analysis of Research on Innovation in New Product Development*

This research on studies that have empirically examined the construct innovation provides a meta-analysis of the marketing, management, and new product literatures. The study extends previous meta-analytic works by drawing on 70 independent samples from 64 studies (published from 1970 to 2006) with a total sample size of 12,921. The overall objective is to propose a synthesized model that includes technological turbulence, market turbulence, customer orientation, competitor orientation, organizational structure, innovation, and new product performance. Six baseline hypotheses were developed and tested. The goal is not only to derive empirical generalizations from these literatures but also to investigate sources of inconsistencies in the findings. Four substantive and two methodological artifacts were tested to determine whether they moderate model relationships (i.e., whether the effect sizes differ for any of the six baseline hypotheses). The potential moderators were project versus program level of analysis, the nature of change required by the innovation, service versus product, country of the data's origin, continuous versus categorical measurement, and the number of scales used. From a theoretical perspective, the results corroborated the resource-based view framework regarding the determinants and the performance outcome of innovation. New product performance (the performance outcome) is a direct consequence of innovation, and this effect is stronger when the data are collected from Western countries. This relationship holds regardless of whether the level of analysis is the new product program versus project or whether the innovation is a product or a service, a robust result relevant to researchers and managers alike. As for the determinants of innovation, the results were as follows. While market turbulence is overall not a direct antecedent to innovation, technological turbulence is overall positively related (especially when market discontinuities are considered or when the data are collected from Asian countries). Customer orientation encourages new product innovation overall, but especially at the program (as opposed to project) level in Western countries. The effect of competitor orientation is also positive. The results for either orientation construct or either turbulence construct held whether the level of analysis was project versus program or whether services versus products were examined. However, the relationship of mechanistic organizational structures to innovation, although positive in the overall sample, did vary by product (positive) versus service (negative).
CMU Informedia's TRECVID 2005 Skirmishes

Runid: Bashful: probabilistic camera motion with conservative threshold 1 for high precision Runid: Doc: probabilistic camera motion with conservative threshold 2 for high precision Runid: Dopey: probabilistic camera motion with relaxed constraints (threshold 1) for high recall Runid: Grumpy: probabilistic camera motion with relaxed constraints (threshold 2) for high recall Runid: Happy: optical flow with weighting 1 Runid: Sleepy: optical flow with weighting 2 Runid: Sneezy: a more sensitive algorithm based on optical flow in order to improve recall