Context-Based e2e Autonomous Operation in B5G Networks.

The research and innovation related to fifth-generation (5G) networks that has been carried out in recent years has decided on the fundamentals of the smart slice in radio access networks (RANs), as well as the autonomous fixed network operation. One of the most challenging objectives of beyond 5G (B5G) and sixth-generation (6G) networks is the deployment of mechanisms that enable smart end-to-end (e2e) network operation, which is required for the achievement of the stringent service requirements of the envisioned use cases to be supported in the short term. Therefore, smart actions, such as dynamic capacity allocation, flexible functional split, and dynamic slice management need to be performed in tight coordination with the autonomous capacity management of the fixed transport network infrastructure. Otherwise, the benefits of smart slice operation (i.e., cost and energy savings while ensuring per-slice service requirements) might be cancelled due to uncoordinated autonomous fixed network operation. Notably, the transport network in charge of supporting slices from the user equipment (UE) to the core expands across access and metro fixed networks. The required coordination needs to be performed while keeping the privacy of the radio and fixed network domains, which is important in multi-tenant scenarios where both network segments are managed by different operators. In this paper, we propose a novel approach that explores the concept of context-aware network operation, where the slice control anticipates the aggregated and anonymized information of the expected slice operation that is sent to the fixed network orchestrator in an asynchronous way. The context is then used as the input for the artificial intelligence (AI)-based models used by the fixed network control for the predictive capacity management of optical connections in support of RAN slices. This context-aware network operation aims at enabling accurate and reliable autonomous fixed network operation under extremely dynamic traffic originated by smart RAN operation. The exhaustive numerical results show that slice context availability improves the benchmarking fixed network predictive methods (90% reduction in prediction maximum error) remarkably in the foreseen B5G scenarios, for both access and metro segments and in heterogeneous service demand scenarios. Moreover, context-aware network operation enables robust and efficient operation of optical networks in support of dense RAN cells (>32 base stations per cell), while the benchmarking methods fail to guarantee different operational objectives.

Drug utilization analysis of osteoporosis medications in seven European electronic health databases.

We studied the characteristics of patients prescribed osteoporosis medication and patterns of use in European databases. Patients were mostly female, older, had hypertension. There was suboptimal persistence particularly for oral medications. Our findings would be useful to healthcare providers to focus their resources on improving persistence to specific osteoporosis treatments. PURPOSE: To characterise the patients prescribed osteoporosis therapy and describe the drug utilization patterns. METHODS: We investigated the treatment patterns of bisphosphonates, denosumab, teriparatide, and selective estrogen receptor modulators (SERMs) in seven European databases in the United Kingdom, Italy, the Netherlands, Denmark, Spain, and Germany. In this cohort study, we included adults aged ≥ 18 years, with ≥ 1 year of registration in the respective databases, who were new users of the osteoporosis medications. The study period was between 01 January 2018 to 31 January 2022. RESULTS: Overall, patients were most commonly initiated on alendronate. Persistence decreased over time across all medications and databases, ranging from 52-73% at 6 months to 29-53% at 12 months for alendronate. For other oral bisphosphonates, the proportion of persistent users was 50-66% at 6 months and decreased to 30-44% at 12 months. For SERMs, the proportion of persistent users at 6 months was 40-73% and decreased to 25-59% at 12 months. For parenteral treatment groups, the proportions of persistence with denosumab were 50-85% (6 month), 30-63% (12 month) and with teriparatide 40-75% (6 month) decreasing to 21-54% (12 month). Switching occurred most frequently in the alendronate group (2.8-5.8%) and in the teriparatide group (7.1-14%). Switching typically occurred in the first 6 months and decreased over time. Patients in the alendronate group most often switched to other oral or intravenous bisphosphonates and denosumab. CONCLUSION: Our results show suboptimal persistence to medications that varied across different databases and treatment switching was relatively rare.

Deep Learning-Based Adaptive Compression and Anomaly Detection for Smart B5G Use Cases Operation.

The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of network resources in the next decades. Among different B5G use cases, the Digital Twin (DT) has been identified as a key high bandwidth-demanding use case. The creation and operation of a DT require the continuous collection of an enormous and widely distributed amount of sensor telemetry data which can overwhelm the transport layer. Therefore, the reduction in such transported telemetry data is an essential objective of smart use case operation. Moreover, deep telemetry data analysis, i.e., anomaly detection, can be executed in a hierarchical way to reduce the processing needed to perform such analysis in a centralized way. In this paper, we propose a smart management system consisting of a hierarchical architecture for telemetry sensor data analysis using deep autoencoders (AEs). The system contains AE-based methods for the adaptive compression of telemetry time series data using pools of AEs (called AAC), as well as for anomaly detection in single (called SS-AD) and multiple (called MS-AGD) sensor streams. Numerical results using experimental telemetry data show compression ratios of up to 64% with reconstruction errors of less than 1%, clearly improving upon the benchmark state-of-the-art methods. In addition, fast and accurate anomaly detection is demonstrated for both single and multiple-sensor scenarios. Finally, a great reduction in transport network capacity resources of 50% and more is obtained by smart use case operation for distributed DT scenarios.

Investigating Imperfect Cloning for Extending Quantum Communication Capabilities.

Quantum computing allows the implementation of powerful algorithms with enormous computing capabilities and promises a secure quantum Internet. Despite the advantages brought by quantum communication, certain communication paradigms are impossible or cannot be completely implemented due to the no-cloning theorem. Qubit retransmission for reliable communications and point-to-multipoint quantum communication (QP2MP) are among them. In this paper, we investigate whether a Universal Quantum Copying Machine (UQCM) generating imperfect copies of qubits can help. Specifically, we propose the Quantum Automatic Repeat Request (QARQ) protocol, which is based on its classical variant, as well as to perform QP2MP communication using imperfect clones. Note that the availability of these protocols might foster the development of new distributed quantum computing applications. As current quantum devices are noisy and they decohere qubits, we analyze these two protocols under the presence of various sources of noise. Three major quantum technologies are studied for these protocols: direct transmission (DT), teleportation (TP), and telecloning (TC). The Nitrogen-Vacancy (NV) center platform is used to create simulation models. Results show that TC outperforms TP and DT in terms of fidelity in both QARQ and QP2MP, although it is the most complex one in terms of quantum cost. A numerical study shows that the QARQ protocol significantly improves qubit recovery and that creating more clones does not always improve qubit recovery.

Supporting Heterogenous Traffic on Top of Point-to-Multipoint Light-Trees.

New 5 G and beyond services demand innovative solutions in optical transport to increase efficiency and flexibility and reduce capital (CAPEX) and operational (OPEX) expenditures to support heterogeneous and dynamic traffic. In this context, optical point-to-multipoint (P2MP) connectivity is seen as an alternative to provide connectivity to multiple sites from a single source, thus potentially both reducing CAPEX and OPEX. Digital subcarrier multiplexing (DSCM) has been shown as a feasible candidate for optical P2MP in view of its ability to generate multiple subcarriers (SC) in the frequency domain that can be used to serve several destinations. This paper proposes a different technology, named optical constellation slicing (OCS), that enables a source to communicate with multiple destinations by focusing on the time domain. OCS is described in detail and compared to DSCM by simulation, where the results show that both OCS and DSCM provide a good performance in terms of the bit error rate (BER) for access/metro applications. An exhaustive quantitative study is afterwards carried out to compare OCS and DSCM considering its support to dynamic packet layer P2P traffic only and mixed P2P and P2MP traffic; throughput, efficiency, and cost are used here as the metrics. As a baseline for comparison, the traditional optical P2P solution is also considered in this study. Numerical results show that OCS and DSCM provide a better efficiency and cost savings than traditional optical P2P connectivity. For P2P only traffic, OCS and DSCM are utmost 14.6% more efficient than the traditional lightpath solution, whereas for heterogeneous P2P + P2MP traffic, a 25% efficiency improvement is achieved, making OCS 12% more efficient than DSCM. Interestingly, the results show that for P2P only traffic, DSCM provides more savings of up to 12% than OCS, whereas for heterogeneous traffic, OCS can save up to 24.6% more than DSCM.

Accurate Low Complex Modulation Format and Symbol Rate Identification for Autonomous Lightpath Operation.

Network automation promises to reduce costs while guaranteeing the required performance; this is paramount when dealing with the forecasted highly dynamic traffic that will be generated by new 5G/6G applications. In optical networks, autonomous lightpath operation entails that the optical receiver can identify the configuration of a received optical signal without necessarily being configured from the network controller. This provides relief for the network controller from real-time operation, and it can simplify the operation in multi-domain scenarios, where an optical connection spans across more than one domain. Consequently, in this work, we propose a blind and low complex modulation format (MF) and symbol rate (SR) identification algorithm. The algorithm is based on studying the effects of decoding an optical signal with different MFs and SRs. Extensive MATLAB-based simulations have been carried out which consider a coherent wavelength division multiplexed system based on 32 and 64 quadrature amplitude modulated signals at up to 96 GBd, thus enabling bit rates of up to 800 Gb/s/channel. The results show remarkable identification accuracy in the presence of linear and nonlinear noise for a wide range of feasible configurations.

Packet Flow Capacity Autonomous Operation Based on Reinforcement Learning.

As the dynamicity of the traffic increases, the need for self-network operation becomes more evident. One of the solutions that might bring cost savings to network operators is the dynamic capacity management of large packet flows, especially in the context of packet over optical networks. Machine Learning, particularly Reinforcement Learning, seems to be an enabler for autonomicity as a result of its inherent capacity to learn from experience. However, precisely because of that, RL methods might not be able to provide the required performance (e.g., delay, packet loss, and capacity overprovisioning) when managing the capacity of packet flows, until they learn the optimal policy. In view of that, we propose a management lifecycle with three phases: (i) a self-tuned threshold-based approach operating just after the packet flow is set up and until enough data on the traffic characteristics are available; (ii) an RL operation based on models pre-trained with a generic traffic profile; and (iii) an RL operation with models trained for real traffic. Exhaustive simulation results confirm the poor performance of RL algorithms until the optimal policy is learnt and when traffic characteristics change over time, which prevents deploying such methods in operators' networks. In contrast, the proposed lifecycle outperforms benchmarking approaches, achieving noticeable performance from the beginning of operation while showing robustness against traffic changes.

BeST-Graft viewer, a new system to improve the bone allograft-recipient matching process.

INTRODUCTION: Tissue establishments are responsible for processing, testing, preserving, storing, and distributing allografts from donors to be transplanted into recipients. In some situations, a matching process is required to determine the allograft that best fits the recipient. Allograft morphology is a key consideration for the matching process. The manual procedures applied to obtain these parameters make the process error-prone. MATERIAL AND METHODS: A new system to manage bone allograft-recipient matching for tissue establishments is proposed. The system requires bone allografts to be digitalized and the resulting images to be stored in a DICOM file. The system provides functionalities to: (i) manage DICOM files (registered in the PACs) from both allografts and recipients; (ii) reconstruct 3D models from DICOM images; (iii) explore 3D models using 2D, 3D, and multiplanar reconstructions; (iv) take allograft and recipient measurements; and (v) visualize and interact with recipient and allograft data simultaneously. The system has been installed in the Barcelona Tissue Bank (Banc de Sang i Teixits), which has digitalized the bone allografts to test the system. RESULTS: A use case with a femur is presented to test all the viewer functionalities. In addition, the recipient-allograft workflow is evaluated to show the steps of the procedure where the viewer can be used. CONCLUSIONS: The bone allograft-recipient matching procedure can be optimized using software tools with functionalities to visualize, interact, and take measurements.

Starviewer and its comparison with other open-source DICOM viewers using a novel hierarchical evaluation framework.

METHODS: The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible. RESULTS: Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8). CONCLUSIONS: Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models.

Characterization of the carbapenem-hydrolyzing oxacillinase oxa-58 in an Acinetobacter genospecies 3 clinical isolate.

Based on imipenem resistance in an Acinetobacter genospecies 3 clinical isolate, we were able to identify, for the first time in this genomic species, a plasmid-encoded bla(OXA-58) gene that was 100% homologous to the same gene in Acinetobacter baumannii.

Characterization of the carbapenem-hydrolyzing oxacillinase OXA-58 in an Acinetobacter phenon 6/ct13TU clinical isolate.

The bla(OXA-58) gene identified in the Acinetobacter phenon 6/ct13TU clinical isolate presented 100% homology with the same gene in Acinetobacter baumannii. Its location in a plasmid suggests that these resistance genes may be transferred from 1 species to another.

Prevalence of IS(Aba1) in epidemiologically unrelated Acinetobacter baumannii clinical isolates.

Seventy-five Acinetobacter baumannii strains belonging to different pulsetypes, plus one ceftazidime-susceptible strain, from a pulsetype in which all strains were resistant, were included in this study. The minimum inhibitory concentration of ceftazidime was determined by the microdilution method. The bla(ADC)-like gene, the IS(Aba1) element and the IS(Aba1) located in the bla(ADC)-like promoter were detected by PCR. The objective of the study was to determine the prevalence of IS(Aba1) in a collection of epidemiologically unrelated A. baumannii clinical isolates. The bla(ADC)-like gene was detected in 74 (97.3%) out of the 76 strains analysed. In these 74 strains, 51 (69%) were positive for the IS element and it was not detected in 23 (31%) strains. Among the A. baumannii strains containing the IS element, 40 (78.4%) had the IS element located in the promoter region of the bla(ADC)-like gene. In a high percentage of A. baumannii clinical isolates carrying the IS(Aba1), this is inserted into the promoter region of the bla(ADC)-like gene. In addition, two clinical isolates belonging to the same pulsetype, one with and one without the IS(Aba1), can be found in the clinical setting, suggesting the potential acquisition or loss of this genetic element in the hospital environment.

How willing are adolescents to record their dietary intake? The mobile food record.

BACKGROUND: Accurately assessing the diets of children and adolescents can be problematic. Use of technologies, such as mobile apps designed to capture food and beverages consumed at eating occasions with images taken using device-embedded cameras, may address many of the barriers to gathering accurate dietary intake data from adolescents. OBJECTIVE: The objectives of this study were to assess the willingness of adolescents to take images of food and beverages at their eating occasions using a novel mobile food record (mFR) and to evaluate the usability of the user confirmation component of the mFR app, referred to as the "review process." METHODS: Mixed methods combining quantitative and qualitative protocols were used in this study. Adolescents (11-15-year olds) attending a summer camp were recruited to participate in the study. First, the participants were asked to take images of foods and beverages consumed as meals and snacks for 2 consecutive days using the mFR app running on an iPhone and the number of images taken was noted. This was followed by focus group sessions to evaluate usability, which was analyzed by content and themes. After using the mFR, a think-aloud method was used to evaluate the usability of the mFR method for reviewing system-identified foods (ie, the review process). A usability questionnaire was administered at the end of all activities. RESULTS: The mFR was accepted by the majority of the 24 boys and 17 girls (n=41) but varied according to gender and eating occasion. Girls were significantly more likely than boys to capture images of their eating occasions (Fisher exact test, P=.03). Participants were more likely to take images of their breakfasts (90%, 36/40) and lunches (90%, 72/80) and least likely to capture afternoon and evening snacks, 54% (43/80) and 40% (32/80), respectively. The major themes from the focus groups with regard to using the mFR were games, rewards, and the need to know more about why they were using the app. Results of the usability questionnaire indicated that including a game component would be important to increase willingness to use the mFR, and a high majority of the participants indicated a willingness to use the mFR for 7 days or more. The image review process was found to be easy to use except for some confusion with overlapping markers on the screen. CONCLUSIONS: The adolescents' experiences with and feedback about the mFR highlighted the importance of increased training, reminders, entertainment (eg, games), and training with practice in using the device to capture complete dietary intake as part of their active lifestyles.

Information theory-based automatic multimodal transfer function design.

In this paper, we present a new framework for multimodal volume visualization that combines several information-theoretic strategies to define both colors and opacities of the multimodal transfer function. To the best of our knowledge, this is the first fully automatic scheme to visualize multimodal data. To define the fused color, we set an information channel between two registered input datasets, and afterward, we compute the informativeness associated with the respective intensity bins. This informativeness is used to weight the color contribution from both initial 1-D transfer functions. To obtain the opacity, we apply an optimization process that minimizes the informational divergence between the visibility distribution captured by a set of viewpoints and a target distribution proposed by the user. This distribution is defined either from the dataset features, from manually set importances, or from both. Other problems related to the multimodal visualization, such as the computation of the fused gradient and the histogram binning, have also been solved using new information-theoretic strategies. The quality and performance of our approach are evaluated on different datasets.

Automatic transfer functions based on informational divergence.

In this paper we present a framework to define transfer functions from a target distribution provided by the user. A target distribution can reflect the data importance, or highly relevant data value interval, or spatial segmentation. Our approach is based on a communication channel between a set of viewpoints and a set of bins of a volume data set, and it supports 1D as well as 2D transfer functions including the gradient information. The transfer functions are obtained by minimizing the informational divergence or Kullback-Leibler distance between the visibility distribution captured by the viewpoints and a target distribution selected by the user. The use of the derivative of the informational divergence allows for a fast optimization process. Different target distributions for 1D and 2D transfer functions are analyzed together with importance-driven and view-based techniques.

Molecular epidemiology and characterization of resistance mechanisms to various antimicrobial agents in Acinetobacter baumannii isolated in Mérida, Venezuela.

BACKGROUND: A. baumannii outbreaks are difficult to control because of the relative ease with which this microorganism spreads and persists in hospital settings. Successive papers reported increased resistance in clinical isolates of A. baumannii, currently resistant to most antibiotics. The purpose of this study was to characterize the epidemiological relationship and the mechanisms of resistance to several antimicrobial agents of a collection of A. baumannii strains. MATERIAL/METHODS: Twenty A. baumannii isolated from two intensive care units (ICUs) at the Instituto Autónomo Universitario de Los Andes, Mérida, Venezuela, were analyzed by PFGE. Characterization of resistance determinants to various antimicrobial agents was also carried out. RESULTS: PFGE typing revealed five different patterns. Pattern 1, susceptible to ciprofloxacin and cefepime, was found to be spread among the patients of both ICUs and was also cultured from a humidifier in the neonatal ICU. All the strains were resistant to gentamicin and tetracycline, 90% to amikacin and cefotaxime, and 85% to ciprofloxacin. The resistance of the strains to ceftazidime, cefepime, and imipenem was 40, 50, and 10%, respectively. All the strains showed beta-lactamases with Ips equal to 5.4 (TEM-1) and greater than 9. Furthermore, two of them, both exhibiting resistance to imipenem, presented a beta-lactamase with an Ip of 7.2 (OXA-58). Three of seven amikacin-resistant A. baumannii strains (PFGE-2) carried the gene encoding the APH(3')-Vla enzyme and two strains (PFGE-5) had the TET(B) determinant. CONCLUSIONS: This study shows the dissemination of A. baumannii clinical isolates, a humidifier being the source of the strain.