Miracle-dz/UniFAR-FTUs huggingface dataset:
Atelectasis and survival after bronchoscopic lung volume reduction for COPD

Bronchoscopic therapies to reduce lung volumes in chronic obstructive pulmonary disease are intended to avoid the risks associated with lung volume reduction surgery (LVRS) or to be used in patient groups in whom LVRS is not appropriate. Bronchoscopic lung volume reduction (BLVR) using endobronchial valves to target unilateral lobar occlusion can improve lung function and exercise capacity in patients with emphysema. The benefit is most pronounced in, though not confined to, patients where lobar atelectasis has occurred. Few data exist on their long-term outcome. 19 patients (16 males; mean±sd forced expiratory volume in 1 s 28.4±11.9% predicted) underwent BLVR between July 2002 and February 2004. Radiological atelectasis was observed in five patients. Survival data was available for all patients up to February 2010. None of the patients in whom atelectasis occurred died during follow-up, whereas eight out of 14 in the nonatelectasis group died (Chi-squared p = 0.026). There was no significant difference between the groups at baseline in lung function, quality of life, exacerbation rate, exercise capacity (shuttle walk test or cycle ergometry) or computed tomography appearances, although body mass index was significantly higher in the atelectasis group (21.6±2.9 versus 28.4±2.9 kg·m−2; p<0.001). The data in the present study suggest that atelectasis following BLVR is associated with a survival benefit that is not explained by baseline differences.
The Use of Ensemble Empirical Mode Decomposition With Canonical Correlation Analysis as a Novel Artifact Removal Technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results.
Dopaminergic Genes Predict Individual Differences in Susceptibility to Confirmation Bias

The striatum is critical for the incremental learning of values associated with behavioral actions. The prefrontal cortex (PFC) represents abstract rules and explicit contingencies to support rapid behavioral adaptation in the absence of cumulative experience. Here we test two alternative models of the interaction between these systems, and individual differences thereof, when human subjects are instructed with prior information about reward contingencies that may or may not be accurate. Behaviorally, subjects are overly influenced by prior instructions, at the expense of learning true reinforcement statistics. Computational analysis found that this pattern of data is best accounted for by a confirmation bias mechanism in which prior beliefs—putatively represented in PFC—influence the learning that occurs in the striatum such that reinforcement statistics are distorted. We assessed genetic variants affecting prefrontal and striatal dopaminergic neurotransmission. A polymorphism in the COMT gene (rs4680), associated with prefrontal dopaminergic function, was predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their veracity accumulated. Polymorphisms in genes associated with striatal dopamine function (DARPP-32, rs907094, and DRD2, rs6277) were predictive of learning from positive and negative outcomes. Notably, these same variants were predictive of the degree to which such learning was overly inflated or neglected when outcomes are consistent or inconsistent with prior instructions. These findings indicate dissociable neurocomputational and genetic mechanisms by which initial biases are strengthened by experience.
EPIC Modeling of a Two-Talker CRM Listening Task

An extension of the auditory module in EPIC is introduced to model the two-talker coordinate response measure (CRM) listening task. The construct of an auditory stream is employed as an object in the working memory of EPIC’s cognitive processor. Production rules are developed that execute the two-talker CRM task. Analysis of these rules reveal two sources of possible error in the output of the auditory processor to working memory. Each is explored in turn and the production rules modified to provide a corpus-driven model that accounts for human performance in the listening task.
Atmospheric Proton and Helium Fluxes Compared to AIRES Simulation Results

Air shower simulation programs are important tools for estimating distributions of particles of different kinds, and that can be measured experimentally. The region of interest spans many orders of magnitude in primary energy, from atmospheric fluxes measured in balloon–borne experiments up to the highest energy cosmic rays detected at the Auger Observatory, for example. The comparison of observed rates of atmospheric neutrino interactions with calculated ones also requires accurate air shower simulations. In this paper we compare the CAPRICE98 results on atmospheric fluxes of protons and alpha particles with results from the AIRES simulation program. The energy range depends on the residual atmosphere and on the kind of particle. Detailed measurements of atmospheric fluxes allow fine–tuning of the models used in the air shower simulations.
TCP SYN Flooding Attacks and Common Mitigations

This document describes TCP SYN flooding attacks, which have been well-known to the community for several years. Various countermeasures against these attacks, and the trade-offs of each, are described. This document archives explanations of the attack and common defense techniques for the benefit of TCP implementers and administrators of TCP servers or networks, but does not make any standards-level recommendations. This memo provides information for the Internet community.
External financing: Market timing or managerial optimism

Management of capital structure is an important part of maximizing the firm value. Financial research has proposed many theories that explain aspects of firm behavior when a firm makes financial decisions that change the firm's capital structure. However, none of the theories fully explain why firms with similar fundamental characteristics make different financing choices. This study focuses on what motivates managers when they are making external financing decisions. It investigated whether the motivation for the decisions about capital structure are driven by market timing or managerial overoptimism. This is done by focusing on equity and debt issues and whether these issues bring the firms closer to or farther away from their optimal capital structure. This study finds that the excess leverage proxy is negatively and significantly related to the one, two, and three year post-financing buy-and-hold abnormal returns even when firm characteristics are controlled. These results are also found when nonissuing matched firms, small firms, and large firms are analyzed. These results are consistent with the Managerial Overoptimism Theory. The results of this study also show that in the first post-financing year firms that issue equity when they are predicted to issue debt significantly out-perform
Applicability analysis of grid security mechanisms on cloud networking

Grid computing has been around for quite a while. It facilitates utilization of distributed resources and has been extremely popular in its implementation. Grids have evolved enough to secure their operational architecture. On the other hand, cloud computing offers more recent alternative in distributed virtualization of resources, providing an on-demand architecture with a simple model for service charges. However, cloud computing is still struggling with different approaches to secure its operations. This paper discusses the security mechanisms in grid and cloud computing, and based on the current implementations in grid security, proposes a simple architecture for secured access control and policy enforcement system for cloud networks.
Local Signal Equalization for Correspondence Matching

Correspondence matching is one of the most common problems in computer vision, and it is often solved using photo-consistency of local regions. These approaches typically assume that the frequency content in the local region is consistent in the image pair, such that matching is performed on similar signals. However, in many practical situations this is not the case, for example with low depth of field cameras a scene point may be out of focus in one view and in-focus in the other, causing a mismatch of frequency signals. Furthermore, this mismatch can vary spatially over the entire image. In this paper we propose a local signal equalization approach for correspondence matching. Using a measure of local image frequency, we equalize local signals using an efficient scale-space image representation such that their frequency contents are optimally suited for matching. Our approach allows better correspondence matching, which we demonstrate with a number of stereo reconstruction examples on synthetic and real datasets.
STRAIGHT model for voice conversion based on acoustical universal structure

The existing voice conversion (VC) systems, those based on Gaussian mixture models (GMM), bring the problems of over smoothing of GMM mapping. With an aim towards resolving these problems, this paper provides a method on Acoustical Universal Structure (ASU) that can be applied to voice conversion based on GMM. Our contributions include: 1) speech transformation and representation using adaptive interpolation of weighted-spectrum (STRAIGHT) model is taken which allows flexible manipulation of speech parameters such as pitch, vocal tract length, and speaking rate while maintaining high reproduction quality; 2) The advantage of the paper is attributed to the introduction of the predictable spectrum, the ASU, in this paper, is introduced to form the mapping relationship between the source speaker and target speaker. 3) In the training phase, the feedback strategy is adopted, which guarantee the smooth translation of spectral parameters between frames. Experimental results indicate that the performance of VC can be dramatically improved by the proposed method in view of speech quality, conversion accuracy and naturalness for speaker individuality from the objective and subjective tests.
Query by Humming System

A Query by Humming system allows the user to find a song by humming part of the tune. No musical training is needed. The idea is simple: you hum into the microphone, the computer records the hum and extracts certain features corresponding to the melody and rhythm characteristics, and it then compares the features to the features of the songs in the database. Finally it returns a ranked list of the songs or song segments most similar to the humming. The goal is to build a reliable and efficient large- scale system that collects thousands of songs and responds in seconds.
The Intrinsic Antiviral Defense to Incoming HSV-1 Genomes Includes Specific DNA Repair Proteins and Is Counteracted by the Viral Protein ICP0

Cellular restriction factors responding to herpesvirus infection include the ND10 components PML, Sp100 and hDaxx. During the initial stages of HSV-1 infection, novel sub-nuclear structures containing these ND10 proteins form in association with incoming viral genomes. We report that several cellular DNA damage response proteins also relocate to sites associated with incoming viral genomes where they contribute to the cellular front line defense. We show that recruitment of DNA repair proteins to these sites is independent of ND10 components, and instead is coordinated by the cellular ubiquitin ligases RNF8 and RNF168. The viral protein ICP0 targets RNF8 and RNF168 for degradation, thereby preventing the deposition of repressive ubiquitin marks and counteracting this repair protein recruitment. This study highlights important parallels between recognition of cellular DNA damage and recognition of viral genomes, and adds RNF8 and RNF168 to the list of factors contributing to the intrinsic antiviral defense against herpesvirus infection.
JULIDE: A Software Tool for 3D Reconstruction and Statistical Analysis of Autoradiographic Mouse Brain Sections

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.
Warped Kaluza-Klein dark matter

Warped compactifications of type IIB string theory contain natural dark matter candidates: Kaluza-Klein modes along approximate isometry directions of long warped throats. These isometries are broken by the full compactification, including moduli stabilization; we present a thorough survey of Kaluza-Klein mode decay rates into light supergravity modes and Standard Model particles. We find that these dark matter candidates typically have lifetimes longer than the age of the universe. Interestingly, some choices for embedding the Standard Model in the compactification lead to decay rates large enough to be observed, so this dark matter sector may provide constraints on the parameter space of the compactification.
Dynamic Capacity Provisioning of Heterogeneous Servers

An important technique for saving energy in data centers is consolidating work onto a small number of well utilized servers via dynamic capacity provisioning. A common approach for dynamic capacity provisioning is “receding horizon control” (RHC), which computes the provisioning for the current time by optimizing over a given window of predictions about the future arrivals. In this work, we provide new results characterizing the performance of RHC. We prove that RHC performs well when servers are homogeneous; specifically, it has performance that quickly tends toward optimality as the prediction window increases. However, we also prove that RHC can perform badly when servers are heterogeneous, regardless of the length of the prediction window. This is problematic since in practice there is heterogeneity both within and between data centers. To address this issue, we introduce two variants of RHC that are guaranteed to perform well in heterogeneous settings. Specifically, under both homogeneous and heterogeneous settings, their competitive ratio matches that of RHC in the homogeneous setting.
Protecting Privacy by Multi-dimensional K-anonymity

Privacy protection for incremental data has a great effect on data availability and practicality. K-anonymity is an important approach to protect data privacy in data publishing scenario. However, it is a NP-hard problem for optimal k-anonymity on dataset with multiple attributes. Most partitions in k-anonymity at present are single-dimensional. Now research on k-anonymity mainly focuses on getting high quality anonymity while reducing the time complexity, and new method of realization of k-anonymity properties according to the requirement of published data. Although most k-anonymity algorithms perform well on static data, their effects decrease when they are on the changing data of real world. This paper proposes a multi-dimensional k-anonymity algorithm based on mapping and divide-and-conquer strategy that is feasible and performs much better in k-anonymity. The second main contribution of this paper is an effective k-anonymity method based on incremental local update on large dataset. It incrementally updates the changing dataset, and a threshold is set to assure the stability of update. Neighbor equivalence sets and similar equivalence sets are computed by their position, which not only avoids the cost of recalculation aroused by little change of dataset, but also improves the practical application performance since the dataset satisfies k-anonymity properties. The experiment shows that the proposed algorithm has a better performance in both time cost and anonymity quality, compared to the methods at present.
Evolution of Natural and Artificial Swarms Project for Animal and Machine Intelligence

Ideas from the biology of Social Insects and Computation have had many fruitful interactions. This paper examines Social Insects, the models used to understand them, and how those models in turn influence Computation. Evolution in Social Insects is studied in particular, and in this light, suggestions are made for future interaction of ideas.
Big is Sometimes Best: The Sokoto Caliphate and Economic Advantages of Size in the Textile Industry

The Sokoto Caliphate, established following the 1804 jihad led by Shehu dan Fodio, was the largest single polity in nineteenth century sub-Saharan Africa.2 Considerable economic benefits derived from its very size, and some of these benefits were passed on to producers and consumers throughout the Caliphate and even far beyond, although those who launched the jihad, probably did not have any of these concerns in mind at the time. As the textile industry was one of the most important industries in the Sokoto Caliphate, the size of the Caliphate had enormous economic advantages for the producers of indigo-dyed textiles and for those involved in the textile trade. It brought various cloth producers from very different traditions within the Caliphate together, while also bringing different textile traditions from outside into a new intimacy with these groups. Thus, the quality of cloth improved and the variety increased for textiles produced within the Caliphate as the nineteenth century progressed. The producers of textiles were very quick to realize some of the advantages of the new mega state for their own livelihood. In this paper, I argue that the actual quality of the textiles produced within the Caliphate definitely improved as the nineteenth century progressed, and that this improved quality was accompanied by an increase in a greater variety of different kinds and qualities of cloth which were made available. Furthermore, this expansion in textile production had the added advantage of making textiles which were increasingly cheap and therefore somewhat easier for more individuals to obtain.
Co-expression of six tightly clustered odorant receptor genes in the antenna of the malaria mosquito Anopheles gambiae

The behavior of female malaria mosquitoes, Anopheles gambiae, especially seeking out blood hosts or selecting oviposition sites, highly depends on the detection of relevant odorants by their sense of smell. This is mediated by olfactory sensory neurons (OSNs) which express distinct odorant receptor (OR) types. In the genome of A. gambiae 76 genes have been annotated to encode putative odorant receptors and the majority of these AgOR genes are arranged in clusters. To assess whether clustered AgOR genes are expressed in a characteristic manner we explored the topographic expression pattern of six tightly adjoined AgOR genes in the female antenna. Whole mount fluorescence in situ hybridization experiments were performed to visualize the olfactory neurons which express a distinct AgOR type in order to determine the number and the distribution of the cells. We found that within the thirteen antennal segments about 75 cells contain mRNA for the four receptor types AgOR13, AgOR15, AgOR17 and AgOR55. Moreover, about half of these cells also transcribe mRNA for the subtypes AgOR16 and AgOR47. Subsequent RT-PCR experiments with primer pairs spanning the coding regions of adjacent AgOR genes revealed the existence of polycistronic mRNA. This result indicates that individual genes were not transcribed but mRNA was comprised of coding sequence from several genes within the studied cluster. Taken together, the data indicate a unique principle for the expression of odorant receptor genes arranged in a large cluster and suggest that the corresponding olfactory neurons are endowed with a distinct set of odorant receptor types.
Trusting Online: Nurturing Trust in Virtual Teams

Internet-mediated virtual teamworking is increasingly becoming an integral part of the work life for many people in information societies. This paper reports an investigation on the development of trust relationships in virtual teamworking. The main objectives of this study are to identify forms of trust relationships in virtual teamworking and to understand how such trust relationships operate in this context. The study was carried out in a large company that uses internet-mediated virtual teamworking. This paper offers a theoretical account of trust relationships in virtual teamworking that considers trust as a property of both organizational members and abstract structures of organizations.
Marketing higher education

Higher Education Marketing is a growing field of practice, but suffers from a lack of theoretical discourse. The development of a theoretical discourse for HE Marketing will nurture the development of meaningful marketing practice. The book argues that while HE should not be commoditised, its place in a highly marketised world environment should not be left to chance. It argues that domesticating our own approach to HE marketing is the first step to developing a relevant marketing environment for HE. The book is based on the CORD model, developed by Felix Maringe as part of his PhD thesis which argues for HE marketing to have a focus on the curriculum. It offers both theoretical and practical insights into issues such as institutional positioning; internationalisation of HE; fundraising; pricing HE; reputation management, and enrolment management.