APMEC: An Automated Provisioning Framework for Multi-access Edge Computing

Novel use cases and verticals such as connected cars and human-robot cooperation in the areas of 5G and Tactile Internet can significantly benefit from the flexibility and reduced latency provided by Network Function Virtualization (NFV) and Multi-Access Edge Computing (MEC). Existing frameworks managing and orchestrating MEC and NFV are either tightly coupled or completely separated. The former design is inflexible and increases the complexity of one framework. Whereas, the latter leads to inefficient use of computation resources because information are not shared. We introduce APMEC, a dedicated framework for MEC while enabling the collaboration with the management and orchestration (MANO) frameworks for NFV. The new design allows to reuse allocated network services, thus maximizing resource utilization. Measurement results have shown that APMEC can allocate up to 60% more number of network services. Being developed on top of OpenStack, APMEC is an open source project, available for collaboration and facilitating further research activities

S-PRAC: Fast Partial Packet Recovery with Network Coding in Very Noisy Wireless Channels

Well-known error detection and correction solutions in wireless communications are slow or incur high transmission overhead. Recently, notable solutions like PRAC and DAPRAC, implementing partial packet recovery with network coding, could address these problems. However, they perform slowly when there are many errors. We propose S-PRAC, a fast scheme for partial packet recovery, particularly designed for very noisy wireless channels. S-PRAC improves on DAPRAC. It divides each packet into segments consisting of a fixed number of small RLNC encoded symbols and then attaches a CRC code to each segment and one to each coded packet. Extensive simulations show that S-PRAC can detect and correct errors quickly. It also outperforms DAPRAC significantly when the number of errors is high

Clinical Epidemiological Characteristics and Risk Factors for Severity of SARS-CoV-2 Pneumonia in Pediatric Patients: A Hospital-Based Study in Vietnam

Introduction Coronavirus disease (COVID-19) is an infectious disease caused by SARS-CoV-2, which can cause organ failure in several organs, cardiac problems, or acute respiratory distress syndrome (ARDS). Identifying clinical epidemiological characteristics and risk factors for complications of COVID-19 allows clinicians to diagnose and treat promptly. Objectives This study aims to describe the clinical epidemiological characteristics of COVID-19 and assess risk factors for the severity of SARS-CoV-2 pneumonia in children treated at Haiphong Children\u27s Hospital. Methods A descriptive cross-sectional study was conducted in Haiphong Children\u27s Hospital, Haiphong, Vietnam, for one year, from January 1, 2022, to December 31, 2022. Results In our study, 540 children were evaluated; the male-to-female ratio was 1.48/1; the median age was 23 months (IQR=6-74); Children aged under one year accounted for the highest proportion (n=202; 37.4%); 40 (7.4%) children had underlying illnesses. The number of admitted patients diagnosed with COVID-19 peaked in February 2022. Regarding severity, 380 (70.4%) cases were mild, 136 (25.2%) were moderate, only 24 (4.4%) cases were severe, and no children died. Common symptoms were fever in 483 (89.4%), coughing in 399 (73.9%), and tachypnea in 163 (30.2%) children. Laboratory features: white blood cell count, platelet count, serum CRP, and coagulation test showed little change. Around 116 (21.5%) had lymphopenia and 148 (27.4%) had pneumonia. Patients under one year were approximately 1.64 times more likely to experience pneumonia complications from COVID-19 than those without such a history (OR=1.64, 95%CI = 1.12 - 2.41, p=0.0112). Patients with underlying conditions were approximately 2.08 times more likely to experience pneumonia complications from COVID-19 compared to those without such conditions (OR=2.08, 95%CI =1.08 - 4.02, p=0.0289). Conclusion In COVID-19 pediatric patients, the severity of the disease was mild to moderate without any mortality. Children aged under one year accounted for the highest proportion of all COVID-19 patients. This study found that age under one year and underlying illnesses are related to pneumonia in COVID-19 pediatric patients

The Cenozoic Song Hong and Beibuwan Basins, Vietnam

The Vietnamese offshore margin holds a substantially underexplored petroleum potential. The key to unravelling this potential lies in understanding the tectono-stratigraphic framework of the region including the Cenozoic mechanisms governing syn-rift and source rock deposition. This is essential for prediction of, for instance the presence and nature of source rocks in South-East Asia and possible reservoir intervals in the syn-rift packages. The Vietnamese part of the Song Hong and Beibuwan Basins (Fig. 1) differs from other basins along the western margin of the South China Sea in that the Palaeogene syn-rift succession is sporadically exposed due to uplift and inversion. These exposures provide a unique glimpse into the Cenozoic syn-rift succession of the basin

Fast IMU-based Dual Estimation of Human Motion and Kinematic Parameters via Progressive In-Network Computing

Many applications involve humans in the loop, where continuous and accurate human motion monitoring provides valuable information for safe and intuitive human-machine interaction. Portable devices such as inertial measurement units (IMUs) are applicable to monitor human motions, while in practice often limited computational power is available locally. The human motion in task space coordinates requires not only the human joint motion but also the nonlinear coordinate transformation depending on the parameters such as human limb length. In most applications, measuring these kinematics parameters for each individual requires undesirably high effort. Therefore, it is desirable to estimate both, the human motion and kinematic parameters from IMUs. In this work, we propose a novel computational framework for dual estimation in real-time exploiting in-network computational resources. We adopt the concept of field Kalman filtering, where the dual estimation problem is decomposed into a fast state estimation process and a computationally expensive parameter estimation process. In order to further accelerate the convergence, the parameter estimation is progressively computed on multiple networked computational nodes. The superiority of our proposed method is demonstrated by a simulation of a human arm, where the estimation accuracy is shown to converge faster than with conventional approaches

Conquering hypertension in Vietnam-solutions at grassroots level: study protocol of a cluster randomized controlled trial

BACKGROUND: Vietnam has been experiencing an epidemiologic transition to that of a lower-middle income country with an increasing prevalence of non-communicable diseases. The key risk factors for cardiovascular disease (CVD) are either on the rise or at alarming levels in Vietnam, particularly hypertension (HTN). Inasmuch, the burden of CVD will continue to increase in the Vietnamese population unless effective prevention and control measures are put in place. The objectives of the proposed project are to evaluate the implementation and effectiveness of two multi-faceted community and clinic-based strategies on the control of elevated blood pressure (BP) among adults in Vietnam via a cluster randomized trial design. METHODS: Sixteen communities will be randomized to either an intervention (8 communities) or a comparison group (8 communities). Eligible and consenting adult study participants with HTN (n = 680) will be assigned to intervention/comparison status based on the community in which they reside. Both comparison and intervention groups will receive a multi-level intervention modeled after the Vietnam National Hypertension Program including education and practice change modules for health care providers, accessible reading materials for patients, and a multi-media community awareness program. In addition, the intervention group only will receive three carefully selected enhancements integrated into routine clinical care: (1) expanded community health worker services, (2) home BP self-monitoring, and (3) a storytelling intervention, which consists of interactive, literacy-appropriate, and culturally sensitive multi-media storytelling modules for motivating behavior change through the power of patients speaking in their own voices. The storytelling intervention will be delivered by DVDs with serial installments at baseline and at 3, 6, and 9 months after trial enrollment. Changes in BP will be assessed in both groups at several follow-up time points. Implementation outcomes will be assessed as well. DISCUSSION: Results from this full-scale trial will provide health policymakers with practical evidence on how to combat a key risk factor for CVD using a feasible, sustainable, and cost-effective intervention that could be used as a national program for controlling HTN in Vietnam. TRIAL REGISTRATION: ClinicalTrials.gov NCT03590691 . Registered on July 17, 2018. Protocol version: 6. Date: August 15, 2019

Features of trastuzumab-related cardiac dysfunction: deformation analysis outside left ventricular global longitudinal strain

BackgroundCancer therapy-related cardiac dysfunction due to trastuzumab has been well-known for many years, and echocardiographic surveillance is recommended every 3 months in patients undergoing trastuzumab treatment, irrespective of the baseline cardiotoxicity risk. However, the potential harm and cost of overscreening in low- and moderate-risk patients have become great concerns.ObjectivesThis study aimed to identify the incidence of early cancer therapy-related cardiac dysfunction (CTRCD) and the behaviours of left and right heart deformations during trastuzumab chemotherapy in low- and moderate-risk patients.MethodsWe prospectively enrolled 110 anthracycline-naïve women with breast cancer and cardiovascular risk factors who were scheduled to receive trastuzumab. The left ventricular ejection fraction (LVEF), left ventricular global longitudinal strain (LV-GLS), and right ventricular and left atrial longitudinal strains were evaluated using echocardiography at baseline, before every subsequent cycle and 3 weeks after the final dose of trastuzumab. The baseline risk of CTRCD was graded according to the risk score proposed by the Heart Failure Association (HFA) Cardio-Oncology Working Group and the International Cardio-Oncology Society (ICOS). CTRCD and its severity were defined according to the current European Society of Cardiology (ESC) guidelines.ResultsTwelve (10.9%) patients had asymptomatic CTRCD. All CTRCD occurred sporadically during the first 9 months of the active trastuzumab regimen in both low- and moderate-risk patients. While CTRCD was graded as moderate severity in 41.7% of patients and heart failure therapy was initiated promptly, no irreversible cardiotoxicity or trastuzumab interruption was recorded at the end of follow-up. Among the left and right heart deformation indices, only LV-GLS decreased significantly in the CTRCD group during the trastuzumab regimen.ConclusionsCTRCD is prevalent in patients with non-high-risk breast cancer undergoing trastuzumab chemotherapy. Low- and moderate-risk patients show distinct responses to trastuzumab. The LV-GLS is the only deformation index sensitive to early trastuzumab-related cardiac dysfunction

Network-coded cooperation and multi-connectivity for massive content delivery

[EN] Massive content delivery is in the spotlight of the research community as both data traffic and the number of connected mobile devices are increasing at an incredibly fast pace. The enhanced mobile broadband (eMBB) is one of the main use cases for the fifth generation of mobile networks (5G), which focuses on transmitting greater amounts of data at higher data rates than in the previous generations, but also on increasing the area capacity (given in bits per second per square meter) and reliability. However, the broadcast and multicast implementation in 5G and presents several drawbacks such as unexpected disconnections and the lack of device-specific QoS guarantees. As a result, whenever the exact same content is to be delivered to numerous mobile devices simultaneously, this content must be replicated. Hence, the same number of parallel unicast sessions as users are needed. Therefore, novel systems that provide efficient massive content delivery and reduced energy consumption are needed. In this paper, we present a network-coded cooperation (NCC) protocol for efficient massive content delivery and the analytical model that describes its behavior. The NCC protocol combines the benefits of cooperative architectures known as mobile clouds (MCs) with Random Linear Network Coding (RLNC). Our results show the benefits of our NCC protocol when compared to the establishment of numerous parallel unicast sessions are threefold: offload data traffic from the cellular link, reduce the energy consumption at the cooperating users, and provide throughput gains when the cellular bandwidth is insufficient.This work was supported in part by the European Union's H2020 Research and Innovation Program under Grant H2020-MCSA-ITN-2016-SECRET 722424. The work of Vicent Pla and Jorge Martinez-Bauset was supported under Grant PGC2018-094151-B-I00 and Grant RED2018-102585-T (MCIU/AEI/FEDER,UE)Leyva-Mayorga, I.; Torre, R.; Pla, V.; Pandi, S.; Nguyen, GT.; Martínez Bauset, J.; Fitzek, FHP. (2020). Network-coded cooperation and multi-connectivity for massive content delivery. IEEE Access. 8:15656-15672. https://doi.org/10.1109/ACCESS.2020.29672781565615672