Miracle-dz/UniFAR-FTUs huggingface dataset:
Chartis Measurement of Collateral Ventilation: Conscious Sedation versus General Anesthesia – A Retrospective Comparison

Background: Absence of interlobar collateral ventilation using the Chartis measurement is the key predictor for successful endobronchial valve treatment in severe emphysema. Chartis was originally validated in spontaneous breathing patients under conscious sedation (CS); however, this can be challenging due to cough, mucus secretion, mucosal swelling, and bronchoconstriction. Performing Chartis under general anesthesia (GA) avoids these problems and may result in an easier procedure with a higher success rate. However, using Chartis under GA with positive pressure ventilation has not been validated. Objectives: In this study we investigated the impact of anesthesia technique, CS versus GA, on the feasibility and outcomes of Chartis measurement. Methods: We retrospectively analyzed all Chartis measurements performed at our hospital from October 2010 until December 2017. Results: We analyzed 250 emphysema patients (median forced expiratory volume in 1 s 26%, range 12–52% predicted). In 121 patients (48%) the measurement was performed using CS, in 124 (50%) using GA, and in 5 (2%) both anesthesia techniques were used. In total, 746 Chartis readings were analyzed (432 CS, 277 GA, and 37 combination). Testing under CS took significantly longer than GA (median 19 min [range 5—65] vs. 11 min [3–35], p < 0.001) and required more measurements (3 [1–13] vs. 2 [1–6], p < 0.001). There was no significant difference in target lobe volume reduction after treatment (–1,123 mL [–3,604 to 332] in CS vs. –1,251 mL [–3,333 to –1] in GA, p = 0.35). Conclusions: In conclusion, Chartis measurement under CS took significantly longer and required more measurements than under GA, without a difference in treatment outcome. We recommend a prospective trial comparing both techniques within the same patients to validate this approach.
Performance analysis for multimedia communication systems with a multilayer queuing network model

Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network (MLCSQN) problem. However, the existing analytical methods to MLCSQN model cannot provide satisfactory solution in terms of accuracy, convergence and consideration of interlocking effects. To this end, this paper proposes a heuristic solving method for MLCSQN model to boost the performance prediction of distributed multimedia software systems. The core concept of this method is referred to as the basic model, which can be further decomposed into two sub-models: client sub-model and server sub-model. The client sub-model calculates think time for server sub-model, and the server sub-model calculates waiting time for client sub-model. Using a breadth-first traversal from leaf nodes to the root node and vice versa, the basic model is then adapted to MLCSQN, with net sub-models iteratively resolved. Similarly, the interlocking problem is effectively addressed with the help of the basic model. This analytical solver enjoys advantages of fast convergence, independence on specific average value analysis (MVA) methods and eliminating interlocking effects. Numerical experimental results on accuracy and computation efficiency verify its superiority over anchors.
Mutation of the Surface Layer Protein SlpB Has Pleiotropic Effects in the Probiotic Propionibacterium freudenreichii CIRM-BIA 129

Propionibacterium freudenreichii is a beneficial Gram-positive bacterium, traditionally used as a cheese-ripening starter, and currently considered as an emerging probiotic. As an example, the P. freudenreichii CIRM-BIA 129 strain recently revealed promising immunomodulatory properties. Its consumption accordingly exerts healing effects in different animal models of colitis, suggesting a potent role in the context of inflammatory bowel diseases. This anti-inflammatory effect depends on surface layer proteins (SLPs). SLPs may be involved in key functions in probiotics, such as persistence within the gut, adhesion to host cells and mucus, or immunomodulation. Several SLPs coexist in P. freudenreichii CIRM-BIA 129 and mediate immunomodulation and adhesion. A mutant P. freudenreichii CIRM-BIA 129ΔslpB (CB129ΔslpB) strain was shown to exhibit decreased adhesion to intestinal epithelial cells. In the present study, we thoroughly analyzed the impact of this mutation on cellular properties. Firstly, we investigated alterations of surface properties in CB129ΔslpB. Surface extractable proteins, surface charges (ζ-potential) and surface hydrophobicity were affected by the mutation. Whole-cell proteomics, using high definition mass spectrometry, identified 1,288 quantifiable proteins in the wild-type strain, i.e., 53% of the theoretical proteome predicted according to P. freudenreichii CIRM-BIA 129 genome sequence. In the mutant strain, we detected 1,252 proteins, including 1,227 proteins in common with the wild-type strain. Comparative quantitative analysis revealed 97 proteins with significant differences between wild-type and mutant strains. These proteins are involved in various cellular process like signaling, metabolism, and DNA repair and replication. Finally, in silico analysis predicted that slpB gene is not part of an operon, thus not affecting the downstream genes after gene knockout. This study, in accordance with the various roles attributed in the literature to SLPs, revealed a pleiotropic effect of a single slpB mutation, in the probiotic P. freudenreichii. This suggests that SlpB may be at a central node of cellular processes and confirms that both nature and amount of SLPs, which are highly variable within the P. freudenreichii species, determine the probiotic abilities of strains.
Key-Message Security over State-Dependent Wiretap Channels

The state-dependent (SD) wiretap channel (WTC) with non-causal channel state information (CSI) available at the encoder is considered. An inner bound on the trade-off region between admissible secret key (SK) and secret message (SM) rates is provided. The result is derived under the stringent semantic-security metric. Our inner bound recovers the best-known achievability results for either SK generation, SM transmission, or simultaneous execution of both. Since some of these past benchmarks were derived under weaker security metrics, our results imply that an upgrade to semantic-security is possible without inflicting any rate loss. It is shown that for certain instances of the considered SD-WTC, the derived region is strictly larger than the previously best-known SK-SM trade-off region reported by Prabhakaran et al., and that a recently reported SK rate for this setup cannot be achieved.
Semantic Ontology-Based NFV Service Modeling

Recently, research on methods for reducing CAPEX and OPEX by the use of automation technology in the NFV environment has been conducted actively. In particular, technologies for the standardization and automatic generation of description formats, which describe information on VNF and network service, are actively investigated. This paper conducted data modeling for VNFs management automation and automatic network service generation, using NSD(Network Service Description) data and ontology, and similar VNF reasoning by the use of ontology reasoning technologies was carried out to define and test relationships between ontology nodes
Fuel-optimal look-ahead adaptive cruise control for heavy-duty vehicles

In this paper, we investigate the problem of how to optimally control a heavy-duty vehicle following another one, commonly referred as ad-hoc or non-cooperative platooning. The problem is formulated as an optimal control problem that exploits road topography information and the knowledge of the preceding vehicle speed trajectory to compute the optimal engine torque and gear request for the vehicle under control. The optimal control problem is implemented by dynamic programming and is tested in a simulation study that compares the performance of multiple longitudinal control strategies. The proposed look-ahead adaptive cruise controller is able to achieve fuel saving up to 7% with respect to the use of a reference vehicle-following controller, by combining the benefits of adjusting the inter-vehicular distance according to the future slope with those of alternating phases of throttling and freewheeling (driving in neutral gear).
Performance Evaluation of Kademlia in Mobile Ad Hoc Networks

MANET is a decentralized network optimized for an infrastructure-less area. Its applications are designed to operate in a distributed manner. Peer-to-peer (P2P) overlays are a possible addition to MANETs to aid in managing resources and information sharing in distributed networks. In this paper, the Kademlia P2P overlay is deployed over a dynamic and different MANET underlaying technologies. This overlay was combined with two different types of MANET routing: OLSR and AODV. An extensive evaluation is carried out for the performance of these combinations in different dynamic network settings. The results show that in most cases, Kademlia achieves its best performance when layered over AODV. However, OLSR-based Kademlia outperforms AODV in terms of delay and network load.
Design and Development of a WAVE Simulator Interoperable with Traffic Simulators

Vehicular communication technologies have gained recognition for their potential contribution to the improvement of the road safety and the traffic congestion. Despite the growing research interest in vehicular communications, currently available network simulators have shortcomings with respect to generation of accurate vehicle driving information. In this paper, we present a network simulator that is interoperable with traffic simulators for the purpose of utilizing more accurate vehicle driving information. The carrier sense multiple access with collision avoidance (CSMA/CA) of the IEEE Wireless Access in Vehicular Environment (WAVE) standard is implemented in the network simulator. The interface between the network simulator and the traffic simulator is designed to convert traffic simulation results into an acceptable input format for the network simulator. Our simulation results show that the proposed network simulator successfully demonstrates the inherent characteristic of the CSMA/CA of the IEEE WAVE standard.
Robust Cache-Aided Interference Management Under Full Transmitter Cooperation

In this paper, we look at a wireless network consisting of $K$ fully-cooperating transmitters serving $K$ receivers, each equipped with a cache memory. Each node is equipped with a single antenna and transmitters have access to partial channel state information. For a symmetric setting, we characterize the generalized degrees of freedom (GDoF) up to a constant multiplicative factor. We further show that the characterized order-optimal GDoF is also attained in a decentralized setting, with no coordination during the cache content placement phase.
Prevalence of Respiratory Polyomaviruses Among Pediatric Patients With Respiratory Symptoms in Singapore

Background: Although WU polyomavirus (WU) and KI polyomavirus (KI) have been demonstrated to infect the human respiratory tract, it remains unclear if WU or KI cause human disease. We sought to further investigate the relationship between WU and KI infection and respiratory disease in a pediatric population with respiratory symptoms in Singapore. Methods: We conducted a cross-sectional study of pediatric patients with respiratory symptoms in a Singaporean pediatrics hospital. Upon consent, residual respiratory samples from pediatric inpatients, previously screened for common respiratory viruses, were collected and further screened for WU and KI using qPCR. The amplicons of positive samples were sequenced for confirmation. The severity of a patient's illness was assessed by chart review post-discharge looking for clinical markers of respiratory status such as presenting symptoms, diagnoses, and interventions. Results: From December 2016 to April 2017, 201 patients with residual respiratory samples were enrolled in the study. The average age of all participants recruited was 45 months. WU and KI were detected in 13% (26/201) and 3% (6/201) of patients, respectively. Conducting bivariate and multivariate modeling, patients with WU or KI positivity were not at increased risk of SARI, need for additional oxygen, intravenous fluids, and did not receive additional oral antibiotics or bronchodilators during admission. In contrast, patients with RSV detections were at increased risk of requiring supplemental oxygen during hospital admission. Conclusion: While limited in sample size, our pilot study data do not support the hypothesis that molecular evidence of WU or KI was associated with increased morbidity among a sample of general, pediatric patients with respiratory illness in Singapore.
Angular Momentum based Stabilizing Control of Underactuated Multi-Link Planar Robots with Last Active Joint

For multi-link planar robots moving in the vertical plane with a last active joint, this paper studies how to design angular momentum based stabilizing controllers with a large region of attraction for the upright equilibrium point (UEP) of the robots, where all the links are upright. First, for an $n$-link planar robot, the presented stabilizing control in this paper contains a term compensating the gravitational term related to the last joint and a linear feedback of $2n$ variables, which are the angular momentum of the robot about the first joint, its first-time derivative, its second-time derivative, and the other $(2n-3$) variables to be designed such that the Jacobian matrix of these $2n$ variables is nonsingular at the UEP. Second, as an application, regarding the three-link case, this paper proves that the Jacobian matrix is nonsingular at the UEP regardless of all the mechanical parameters if the three variables to be designed are chosen to be one of the nine combinations of any two joint angles from three joint angles and any one joint angular velocity from three joint angular velocities of the robot. Finally, the simulation results of a three-link robot are presented to show that the regions of attraction of the obtained nine controllers are bigger than that of the conventional linear state-feedback controller with the state variables being the angles and angular velocities of the robot. The new results obtained in this paper include the existing results for the two-link case as a special case.
The Informativeness of $k$ -Means for Learning Mixture Models

The learning of mixture models can be viewed as a clustering problem. Indeed, given data samples independently generated from a mixture of distributions, we often would like to find the <italic>correct target clustering</italic> of the samples according to which component distribution they were generated from. For a clustering problem, practitioners often choose to use the simple <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means algorithm. <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means attempts to find an <italic>optimal clustering</italic> which minimizes the sum-of-squares distance between each point and its cluster center. In this paper, we consider fundamental (i.e., information-theoretic) limits of the solutions (clusterings) obtained by optimizing the sum-of-squares distance. In particular, we provide sufficient conditions for the closeness of any optimal clustering and the correct target clustering assuming that the data samples are generated from a mixture of spherical Gaussian distributions. We also generalize our results to log-concave distributions. Moreover, we show that under similar or even weaker conditions on the mixture model, any optimal clustering for the samples with reduced dimensionality is also close to the correct target clustering. These results provide intuition for the informativeness of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-means (with and without dimensionality reduction) as an algorithm for learning mixture models.
Satellite Support for Enhanced Mobile Broadband Content Delivery in 5G

Satellite communication has recently been included as one of the enabling technologies for 5G backhauling, in particular for the delivery of bandwidth-demanding enhanced mobile broadband (eMBB) application data in 5G. In this paper we introduce a 5G-oriented network architecture empowered by satellite communications for supporting emerging mobile video delivery, which is investigated in the EU 5GPPP Phase 2 SAT5G Project. Two complementary use cases are introduced, including (1) the use of satellite links to support offline multicasting and caching of popular video content at 5G mobile edge, and (2) real-time prefetching of DASH (Dynamic Adaptive Streaming over HTTP) video segments by 5G mobile edge through satellite links. In both cases, the objective is to localize content objects close to consumers in order to achieve assured Quality of Experiences (QoE) in 5G content applications. In the latter case, in order to circumvent the large end-to-end propagation delay of satellite links, testbed based experiments have been carried out to identify specific prefetching policies to be enforced by the Multiaccess computing server (MEC) for minimizing user perceived disruption during content consumption sessions.
A novel research approach to enhance research group-level science data management

This poster will report an alternative approach compared with large-scale collection, technology development, or discipline informatics projects by exploring the enhancement of science data management at the research group level. An academic-year-long project involving both information and technical analysts demonstrated that flexible introduction of IT in the form of a relational database solution presents an opportunity to incorporate data-related practices, behavior, and schemes into a tool. The project team used cognitive work analysis and participatory design research methods to sensitively analyze research practice and then design and introduce a prototype tool. Iterative analysis and design cycles captured and incorporated the complex practices of researchers who struggle with the accumulation of samples and related digital data files from years of research. Design research processes will be analyzed according to project developments and research group reaction to the proposed data management tool design and preliminary attempt at implementation.
Experimental Identification of the Spatial Spillover Operator for Systems with Insuppressible Disturbances

The spatial spillover operator quantifies the relative effectiveness of a controller at two different spatial locations. This operator is relevant to noise and vibration control, where the response of the system at a location without a sensor may be unsatisfactory. Identification of the spatial spillover operator based on a representation involving four transfer functions requires measurements of the disturbances, which may not be available in practice. Likewise, identification based on a representation involving two transmissibilities is not feasible in systems where the disturbance cannot be suppressed. To overcome this difficulty in systems with disturbances that are both unmeasured and insuppressible, this paper considers identification based on a hybrid representation involving one transmissibility and two transfer functions. Acoustic data are used to identify the spillover operator and validate the proposed method.
External Knowledge Absorption in SMEs

External knowledge plays important roles in firms' internal innovation activities. Firms need to develop absorptive capabilities and carefully manage the knowledge absorbing processes to better benefit from external knowledge. This study adopted a qualitative approach to investigate how Chinese SMEs absorb external knowledge. We examined how external knowledge is recognized, assimilated, utilized in a sample of 16 SMEs, and what barriers they may face when absorbing external knowledge. This paper extends current literature on organizational absorptive capabilities by revealing some of the key issues or sub-activities underlying each dimension of the concept of absorptive capabilities.
A novel Empirical Bayes with Reversible Jump Markov Chain in User-Movie Recommendation system

In this article we select the unknown dimension of the feature by re- versible jump MCMC inside a simulated annealing in bayesian set up of collaborative filter. We implement the same in MovieLens small dataset. We also tune the hyper parameter by using a modified empirical bayes. It can also be used to guess an initial choice for hyper-parameters in grid search procedure even for the datasets where MCMC oscillates around the true value or takes long time to converge.
Implementation of an ISDB-TBLDM Broadcast System Using the BICM Stage of ATSC 3.0 on Enhanced Layer and Diversity at Reception

This paper presents performance results of commercial ISDB-TB receivers with the ISDB-TB LDM in Core Layer. The Core Layer is fully compatible with ISDB-TB and is multiplexed with the Enhanced Layer. Simulation results of the Enhanced Layer using a powerful channel coder with modulation up to 256-QNUC and Non-Uniform Constellation are presented. The ISDB-TB LDM can improve the spectral efficiency and useful bit rate so that it becomes possible to use it in the transition for UHDTV applications. The Enhanced Layer uses the same BICM of ATSC 3.0, with LDPC encoder concatenated with the BCH. The implementation was done using the GNU Radio Companion software and Software Defined Radio. The Maximal Ratio Combining technique was proposed to increase the robustness of the system. This solution is an alternative way to introduce a new digital terrestrial broadcasting system using the same channel and infrastructure.
Sparse Transition Matrix Estimation for Sub-Gaussian Autoregressive Processes with Missing Data

High-dimensional time series data exist in numerous areas such as finance, genomics, healthcare, and neuroscience. An unavoidable aspect of all such datasets is missing data, and dealing with this issue has been an important focus in statistics, control, and machine learning. In this work, we consider a high-dimensional estimation problem where a dynamical system, governed by a stable vector autoregressive model, is randomly and only partially observed at each time point. Our task amounts to estimating the transition matrix, which is assumed to be sparse. In such a scenario, where covariates are highly interdependent and partially missing, new theoretical challenges arise. While transition matrix estimation in vector autoregressive models has been studied previously, the missing data scenario requires separate efforts. Moreover, while transition matrix estimation can be studied from a high-dimensional sparse linear regression perspective, the covariates are highly dependent and existing results on regularized estimation with missing data from i.i. d. covariates are not applicable. At the heart of our analysis lies 1) a novel concentration result when the innovation noise satisfies the convex concentration property, as well as 2) a new quantity for characterizing the interactions of the time-varying observation process with the underlying dynamical system.
A note on pseudo‐observations and left‐truncation

Pseudo‐observations have been introduced as a way to perform regression analysis of a mean value parameter related to a right‐censored time‐to‐event outcome, such as the survival probability or the restricted mean survival time. Since the introduction of the approach there have been several extensions from the original setting. However, the proper definition and performance of pseudo‐observations under left‐truncation has not yet been addressed. Here, we look at two types of pseudo‐observations under right‐censoring and left‐truncation. We explored their performance in a simulation study and applied them to data on diabetes patients with left‐truncation.