bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increased nitric oxide in exhaled air in patients with rheumatic heart disease
Authors: Gölbaşl Zehra , Dinçer Sibel , Bayol Hakan , Uğurlu Belgizar , Çiçek Dilek , Keleş Telat , Aydoğdu Sinan , Erbaş Deniz 
Published: July 2002

AbstractBackground:Endogenous production of nitric oxide and its presence in exhaled air was observed in humans. Prior studies have yielded contrasting information about the production of nitric oxide in patients with heart failure.Aims:The aim of this study was to measure nitric oxide in the exhaled air of patients with chronic rheumatic heart disease with and without pulmonary hypertension.Methods:Seventy‐four patients (6 patients had isolated mitral stenosis; 13 patients had combined mitral stenosis and mitral regurgitation; 1 patient had isolated mitral regurgitation; 54 patients had combined mitral and aortic valve disease) and 27 healthy subjects were entered in the study. The nitric oxide concentration in exhaled air was determined with a chemiluminescence analyser. Echocardiography was performed in all patients to assess the severity of the valve disease and for the measurement of pulmonary artery pressure.Results:The level of exhaled nitric oxide was significantly greater in patients with rheumatic heart disease than in controls. The value of nitric oxide concentration in exhaled air was significantly increased in patients with pulmonary hypertension, as compared with patients who had normal pulmonary artery systolic pressure.Conclusion:We found increased nitric oxide in the exhaled air in patients with rheumatic heart disease, especially in those with pulmonary hypertension, compared with healthy patients.
A cost‐effectiveness analysis of bisoprolol for heart failure
Authors: Varney Susan 
Published: July 2002

AbstractAims:This study considers the cost‐effectiveness of bisoprolol in heart failure patients as an adjunctive therapy to usual treatment.Methods and results:A cost‐effectiveness model was constructed using data available from the CIBIS I & II trials and other secondary sources. Differences in patient survival rates were calculated for bisoprolol (n ‐ 1327) and placebo groups (n ‐ 1320) extrapolating data over a 5‐year period, under limited and extended benefits scenarios to calculate life years gained (LYG). Hospitalisation rates were calculated using data from both CIBIS trials. Costs were considered under two different patient management protocols for treatment initiation — shared care by outpatient clinics and GPs and initiation by a nurse working in the community. Discounted LYG were calculated to be 0.228 under the limited benefits scenario and 0.368 under the extended benefits scenario. Under the extended benefits scenario shared care resulted in a cost of £268 per LYG or £412 per LYG for community initiation. Under the limited benefits scenario the costs were a £135 saving and £69, respectively.Conclusion:This analysis has shown bisoprolol to be an economically attractive therapy in comparison with other treatments. It is hoped that its adoption by clinicians will be rapid, despite the labour intensive and time consuming up‐titration process involved in its initiation.
OUTCOMES OF HIGH‐RISK WOMEN CARED FOR BY CERTIFIED NURSE‐MIDWIVES
Authors: Davidson Michele R. 
Published: July 2002

ABSTRACTThis study describes the incidence of specific high‐risk factors of a population cared for by a group of certified nurse‐midwives (CNMs) in a Mid‐Atlantic, inner‐city, nonprofit, hospital‐based clinic. Outcomes were compared with all women who delivered in the United States in 1994. Univariate statistics, which consisted of descriptive statistics, frequencies, and percentage distribution, were used. This comparison suggests that CNMs can provide safe care to women with high‐risk conditions. Outcomes for the midwifery sample were more favorable for vaginal births, vaginal deliveries after cesarean section, forceps‐ and vacuum‐assisted deliveries, cesarean delivery, and 5‐minute Apgar scores. The incidence of maternal fever and meconium stained amniotic fluid was higher. Implications and limitations of the study are discussed.
MassiveIoTConnections
Authors: Li Lingxiang , Chen Shiyu , Chen Zhi , Quek Tony Q.S. 
Published: May 2020

AbstractBy 2020, more than 50 billion internet of things (IoT) devices, ranging from critical IoT applications such as autonomous vehicles, manufacturing automation, and VR/AR to massive IoT applications such as smart home, smart farming, and smart energy, will be connected through radio communications. Cost‐effective connectivity and efficient management of such a huge number of heterogeneous devices are the main enablers for IoT services uptake. 5G is particularly suitable for IoT due to its key features as follows: (i) the integration of heterogeneous low‐power wide area (LPWA) radio access technologies, (ii) the introduction of fog/edge computing that brings the cloud functionalities close to front‐end devices, and (iii) the assistance of machine learning (ML) techniques that allows 5G wireless networks to be predictive and proactive. LPWA technologies can provide low‐rate long‐range radio communications, as a complement to the current cellular connectivity technologies. With the assistance fog/edge computing, the IoT network can scale more easily, and also end users can access the network resources more efficiently. ML helps an IoT network to make smart decisions via learning network uncertainties, planning resource allocations, and configuring the associated network parameters in a constantly varying environment. This article provides a comprehensive survey of these technologies. Specifically, the basic requirements and challenges in an IoT network with massive connections are reviewed. The advantages of using fog/edge‐based and ML‐based approaches are summarized. Furthermore, some potential issues caused by massive IoT connections for future work are also discussed.
Energy Harvesting Networks
Authors: Singh Keshav , Ku Meng‐Lin , Flanagan Mark F. , Li Wei 
Published: May 2020

AbstractIn the era of big data, the rapid growth of data services is pushing forward the persistent evolution of wireless network designs to resolve new challenges such as spectrum efficiency, power consumption, quality‐of‐service (QoS), mobility. In particular, energy consumption issues become critical in many emerging wireless applications, for example, in Internet‐of‐Things (IoT), and motivate researchers to revisit the network designs which take the energy efficiency into consideration. Energy harvesting (EH) has recently been advocated as an alternative to perpetually power wireless nodes in the next‐generation wireless networks, especially for the networks that are confined by limited battery to affect the network lifetime or in the hazardous environments that are inconvenient to frequently replace batteries. The characteristics of various ambient energy sources are introduced with the focus of their impact on wireless communication designs, as compared with the conventional grid power supply. The design issues are then elaborated for various modern wireless networks, including cooperative networks, cognitive radio networks, vehicular networks, underwater networks, and unmanned aerial vehicle (UAV) networks. In particular, two examples regarding with the cooperative communications are provided to get more insight into the methodology for designing EH networks. The design challenges of the incorporation of EH into these wireless networks are highlighted in different EH environments from the underwater, ground to air.
Data Engineering in Autonomic Networking
Authors: Pastor‐Perales Antonio , López Diego R. , Gómez Sandra , Mozo Alberto 
Published: May 2020

AbstractData evidence, supported by appropriate measurements and metadata, is an essential component of any autonomous management applicable to next‐generation networks. To make this data evidence usable, different data engineering techniques have to be applied and, given the nature of network infrastructures and the constraints imposed on them, they cannot be evaluated on running production environments and/or on data directly collected from them. A synthetic data engineering framework, as Telefonica'sMouseworld, is the best choice to accomplish these evolution and validation tasks.The main components of the Mouseworld are described, including a precise example of how the framework capabilities are applied for the automated generation of STAs (Smart Traffic Analyzers), a family of neural networks suitable to become the next generation of traffic classification tools and services. The matters for future consideration in applying data engineering on next‐generation networks, such as telemetry integration, model‐based orchestration, and intent interfaces are discussed at the end of the article.
5G Development: Automation and the Role of Artificial Intelligence
Authors: Kilinc Caner , Sun Chuanhao , Marina Mahesh K. 
Published: May 2020

Abstract5G is expected to be commercially rolled out by 2020 and targets challenging KPI requirements. Due to the increased complexity of the mobile networks, meeting the requirements by the existing manual network operation techniques is infeasible for 5G. Also, the manual daily network operations escalate mobile networks Operation Expenses (OPEX). Without a dramatic increase in OPEX, dealing with the network complexity and meeting the KPIs for each challenging use case is only possible by the realization of autonomous network operation functions. The autonomous networks' components and the intelligent functions are developed with the cutting edge Machine Learning (ML) and Artificial Intelligence (AI) models. Furthermore, to be able to realize the efficient and scalable network automation capabilities, ONAP (Open Network Automation Platform) and OSM (Open Source Management and orchestration) frameworks are proposed for 5G. These frameworks provide a set of plug and play automation functions as well as APIs, which enables the mobile operators to extend the framework capabilities by developing their network automation functions to tackle their individual business and operational challenges. The automated network management and orchestration function, in turn, enables the operators to keep the OPEX to reasonable levels and meet the challenging KPI requirements of 5G. This article as a baseline provides an overview of 4G Long‐Term Evolution (LTE) Self‐Organizing Networks (SON) and presents 5G automation concepts and frameworks. Furthermore, in this article, the prominent 5G automation frameworks namely ONAP and OSM are compared, and evidently, the ONAP framework has enriched network automation functions and stands out as the choice of the majority of the telecommunication industry. Finally, this article summarizes the cutting edges AI models and provides a literature review on AI applications in the scope of mobile network automation.
5G Enabling Technologies and Autonomic Networking
Authors: Carrozzo Gino 
Published: May 2020

Abstract
Upcoming 5G networks are a substantial leap in real converged networks as they support by design a wide range of different services, at scale, with very highly dynamic usage patterns, in massive density, low latency, and very high throughputs. Apart from the radio technology advancements, which will unleash new communication performances, 5G networks and related services are designed to use extensively softwarized network functions to make the overall infrastructure more agile and less costly. The chaining of multiple virtualized network functions for end‐to‐end services and their huge proliferation in multiple per‐tenant instances due to network slicing call for deep use of autonomic networking architectures and techniques to efficiently manage the scale and complexity of network management in 5G contexts.
This article describes the core aspects of autonomic networking for 5G networks, aiming at providing an overview of some recent results of research works in Europe and their relationship to ongoing standardization at ETSI, namely for Zero‐touch Network and Service Management (ZSM) and Experiential Networked Intelligence (ENI).
Resource Allocation in Device‐to‐Device Communications
Authors: Foukalas Fotis 
Published: May 2020

AbstractThe aim of this article is to provide details about the resource allocation in device‐to‐device (D2D) communications. We first present the four different types of mode selection highlighting the main procedures of D2D communications, where two devices can communicate directly to each other. In the sequel, we provide details on the technologies developed under the 3GPP standardization body such as mode selection, network discovery, relay selection and D2D synchronization. We focus on the different type of resource allocations solutions that can be used for the considered technologies that are part of the 3GPP D2D framework. Finally, we discuss the open challenges related to resource allocation in D2D communications with emphasis in V2X communications and mmWave. The conclusion is that we can use different type of solutions for different type of system models depending on the D2D use cases such as V2X, public safety and proximity services.
Interference Management inD2D
Authors: Denis Juwendo , Assaad Mohamad 
Published: May 2020

AbstractDevice‐to‐device (D2D) technology is a promising communication paradigm that enables direct communication between spatially close devices. The D2D technology is very appealing from the standpoint of efficient spatial reuse of resources since it permits to establish communications in networks with higher density of users. Consequently, the introduction of D2D will lead to network performance improvement in terms of spectral and energy efficiency, power consumption, delay reduction, as well as coverage extension. However, implementing D2D technology in 5G networks comes with a set of technical challenges, mainly due to interferences incurred between D2D links and between D2D and cellular users. This article provides a survey of the main interference management frameworks in D2D network in general and underlay D2D communication, in particular. Interference management‐based frameworks can be divided into two main categories: (i) power control and resource management schemes and (ii) advanced physical layer schemes, such as interference cancellation, interference alignment, and multiantenna systems. We provide a brief description of the main studies for the aforementioned categories and discuss the main results.
Mobility Prediction Based Resource Management
Authors: Imran Muhammad , Ozturk Metin , Abubakar Attai I. , Klaine Paulo V. , Hussain Sajjad , Abbasi Qammer H. 
Published: May 2020

AbstractOwing to the challenging nature of emerging applications, such as augmented reality, 4 K video streaming, and remote surgery, 5G networks are expected to deal with a broad range of issues including higher data rate provision, less energy consumption, lower latency, etc.Therefore, intelligent and proactive network management is envisioned to be an integral part of 5G in order to make the communication networks more agile, dynamic, and efficient. In this regard, mobility prediction has gained a significant amount of attention owing to their diverse application domains.This article focuses on discussing the implementation of mobility prediction for resource management in mobile communication networks. After describing the challenges expected from 5G networks with related statistical facts, predictive mobility management is introduced with its distinctive applications.After that, the use of mobility prediction in communication networks is elaborated according to different resource types, such as radio, energy, and built‐in resources, and the corresponding state‐of‐the‐art literature is classified accordingly.
VNFPlacement and Sharing inNFV‐Based Cellular Networks
Authors: Malandrino Francesco , Chiasserini Carla Fabiana 
Published: May 2020

AbstractNetwork function virtualization is one of the most relevant enabling technologies for 5G: conceiving a vertical service as a set of virtual network functions (VNFs) makes it possible to implement a service at the network edge in a fast and flexible manner, using computing, networking, and storage resources available therein. However, while deploying the VNFs composing a service, it is critical (i) to meet the key performance indices required by the vertical and (ii) to use the available resources in the most efficient manner so as to both cope with possible resource shortage and minimize the overall deployment cost.To successfully address the aforementioned issues, several works have tackled the problem of VNF placement at the network edge and, more recently, the problem of VNF sharing, i.e. of reusing the same VNF for multiple concurrent services.In this article, we first introduce VNF placement in 5G cellular networks and review existing solutions to this aspect. Then we focus on the problem of how to efficiently reuse VNFs and how to adapt the resources assigned to the virtual machines where such VNFs run, so that that the vertical key performance indicators (KPIs) are still satisfied. Importantly, it has been shown that carefully prioritizing the traffic of the services sharing a set of VNFs can lead to a significant cost reduction while still meeting the services KPIs. Such priorities can be set through an efficient algorithm, which provides a solution within a constant factor from the optimum, in polynomial time.
Reciprocal Signaling between Myeloid Derived Suppressor and Tumor Cells Enhances Cellular Motility and is Mediated by Structural Cues in the Microenvironment
Authors: Shukla Vasudha C. , Duarte‐Sanmiguel Silvia , Panic Ana , Senthilvelan Abirami , Moore Jordan , Bobba Christopher , Benner Brooke , Carson William E. , Ghadiali Samir N. , Gallego‐Perez Daniel 
Published: May 2020

AbstractMyeloid derived suppressor cells (MDSCs) have gained significant attention for their immunosuppressive role in cancer and their ability to contribute to tumor progression and metastasis. Understanding the role of MDSCs in driving cancer cell migration, a process fundamental to metastasis, is essential to fully comprehend and target MDSC‐tumor cell interactions. This study employs microfabricated platforms, which simulate the structural cues present in the tumor microenvironment (TME) to elucidate the effects of MDSCs on the migratory phenotype of cancer cells at the single cell level. The results indicate that the presence of MDSCs enhances the motility of cancer‐epithelial cells when directional cues (either topographical or spatial) are present. This behavior appears to be independent of cell–cell contact and driven by soluble byproducts from heterotypic interactions between MDSCs and cancer cells. Moreover, MDSC cell‐motility is also impacted by the presence of cancer cells and the cancer cell secretome in the presence of directional cues. Epithelial dedifferentiation is the likely mechanism for changes in cancer cell motility in response to MDSCs. These results highlight the biochemical and biostructural conditions under which MDSCs can support cancer cell migration, and could therefore provide new avenues of research and therapy aimed at stemming cancer progression.
Calcitriol‐Loaded Dual‐pH‐Sensitive Micelle Counteracts Pro‐Metastasis Effect of Paclitaxel in Triple‐Negative Breast Cancer Therapy
Authors: Zheng Zhong , Lang Tianqun , Huang Xin , Wang Guanru , Lee Robert J. , Teng Lesheng , Yin Qi , Li Yaping 
Published: May 2020

AbstractThe therapy of triple‐negative breast cancer (TNBC) relies on chemotherapy basing on cytotoxic agents, including paclitaxel (PTX). Unfortunately, PTX will facilitate the invasion of cancer cells and the formation of metastases. To counteract pro‐metastasis of PTX in TNBC therapy, in this work, calcitriol (CTL) is delivered along with PTX by a dual‐pH‐sensitive micelle. The PTX/CTL‐co‐loaded dual‐pH‐sensitive micelle (PCDM) can switch its surface charge from negative to positive at the tumor tissue and release PTX and CTL inside the lysosomes because of the structure change of the polymers composing PCDM under the acidic condition. This property makes PCDM able to escape from mononuclear‐phagocyte system clearance and easy to enter tumor cells. PCDM efficiently suppresses the 4T1 primary tumor growth in mice and inhibits lung metastasis, due to downregulation of matrix metalloproteinase‐9 and BCL‐2 levels, upregulation of E‐cadherin level, and counteracting the PTX‐induced elevation of C‐C motif chemokine ligand 2 (CCL2) and Ly6C+ monocytes levels by CTL. PCDM shows good biocompatibility without promoting the serum calcium level. Therefore, the combination of PTX and CTL based on this pH‐sensitive micelle is promising for the TNBC treatment.
Embedded Metal Oxide Plasmonics Using Local Plasma Oxidation of AZO for Planar Metasurfaces
Authors: Sun Kai , Xiao Wei , Ye Sheng , Kalfagiannis Nikolaos , Kiang Kian Shen , de Groot C. H.(Kees) , Muskens Otto L. 
Published: May 2020

AbstractNew methods for achieving high‐quality conducting oxide metasurfaces are of great importance for a range of emerging applications from infrared thermal control coatings to epsilon‐near‐zero nonlinear optics. This work demonstrates the viability of plasma patterning as a technique to selectively and locally modulate the carrier density in planar Al‐doped ZnO (AZO) metasurfaces without any associated topographical surface profile. This technique stands in strong contrast to conventional physical patterning which results in nonplanar textured surfaces. The approach can open up a new route to form novel photonic devices with planar metasurfaces, for example, antireflective coatings and multi‐layer devices. To demonstrate the performance of the carrier‐modulated AZO metasurfaces, two types of devices are realized using the demonstrated plasma patterning. A metasurface optical solar reflector is shown to produce infrared emissivity equivalent to a conventional etched design. Second, a multiband metasurface is achieved by integrating a Au visible‐range metasurface on top of the planar AZO infrared metasurface. Independent control of spectral bands without significant cross‐talk between infrared and visible functionalities is achieved. Local carrier tuning of conducting oxide films offers a conceptually new approach for oxide‐based photonics and nanoelectronics and opens up new routes for integrated planar metasurfaces in optical technology.
Liquid‐Phase Electron Microscopy for Soft Matter Science and Biology
Authors: Wu Hanglong , Friedrich Heiner , Patterson Joseph P. , Sommerdijk Nico A. J. M. , de Jonge Niels 
Published: May 2020

AbstractInnovations in liquid‐phase electron microscopy (LP‐EM) have made it possible to perform experiments at the optimized conditions needed to examine soft matter. The main obstacle is conducting experiments in such a way that electron beam radiation can be used to obtain answers for scientific questions without changing the structure and (bio)chemical processes in the sample due to the influence of the radiation. By overcoming these experimental difficulties at least partially, LP‐EM has evolved into a new microscopy method with nanometer spatial resolution and sub‐second temporal resolution for analysis of soft matter in materials science and biology. Both experimental design and applications of LP‐EM for soft matter materials science and biological research are reviewed, and a perspective of possible future directions is given.