Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework

To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open RAN (O-RAN). So far, however, the applicability of O-RAN in controlling and optimizing RAN functions has not been widely investigated. In this paper, we jointly optimize the flow-split distribution, congestion control and scheduling (JFCS) to enable an intelligent traffic steering application in O-RAN. Combining tools from network utility maximization and stochastic optimization, we introduce a multi-layer optimization framework that provides fast convergence, long-term utility-optimality and significant delay reduction compared to the state-of-the-art and baseline RAN approaches. Our main contributions are three-fold: i) we propose the novel JFCS framework to efficiently and adaptively direct traffic to appropriate radio units; ii) we develop low-complexity algorithms based on the reinforcement learning, inner approximation and bisection search methods to effectively solve the JFCS problem in different time scales; and iii) the rigorous theoretical performance results are analyzed to show that there exists a scaling factor to improve the tradeoff between delay and utility-optimization. Collectively, the insights in this work will open the door towards fully automated networks with enhanced control and flexibility. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms in terms of the convergence rate, long-term utility-optimality and delay reduction.Comment: 15 pages, 10 figures. A short version will be submitted to IEEE GLOBECOM 202

Required flows for aquatic ecosystems in Ma River, Vietnam

Ecological flow requirements for the Ma River in dry season were assessed in three reaches of Ma – Buoi, Ma – Len and Ma – Chu. 5 indictor fish species was chosen based on biodiversity survey and roles of those species in aquatic ecosystem as well as local communities. Biological and hydrological data (dry season of 2016- 2017) and 35 year recorded hydrological data were collected and analyzed as input data for a physical habitat model River HYdraulic and HABitat SImulation Model – RHYHABSIM. Model results shown that the optimal flows of the reaches were very much higher compare with the minimum annual low flow - MALF. In this study, MALF7day were applied to calculate the recommended minimum flows of the three reaches. The recommended required minimum flows for Ma – Buoi, Ma – Len and Ma – Chu reaches were 51 m3/s, 49 m3/s and 61 m3/s, respectively. It must be stressed that this study only assessed whether or not there is enough habitat available for the river to sustain a healthy ecosystem

Comparative Analysis of Swine Antibody Responses Following Vaccination with Live-Attenuated and Killed African Swine Fever Virus Vaccines

African swine fever virus (ASFV) is circulating in many swine-producing countries, causing significant economic losses. It is observed that pigs experimentally vaccinated with a live-attenuated virus (LAV) but not a killed virus (KV) vaccine develop solid homologous protective immunity. The objective of this study was to comparatively analyze antibody profiles between pigs vaccinated with an LAV vaccine and those vaccinated with a KV vaccine to identify potential markers of vaccineinduced protection. Thirty ASFV seronegative pigs were divided into three groups: Group 1 received a single dose of an experimental LAV, Group 2 received two doses of an experimental KV vaccine, and Group 3 was kept as a non-vaccinated (NV) control. At 42 days post-vaccination, all pigs were challenged with the parental virulent ASFV strain and monitored for 21 days. All pigs vaccinated with the LAV vaccine survived the challenge. In contrast, eight pigs from the KV group and seven pigs from the NV group died within 14 days post-challenge. Serum samples collected on 41 days post-vaccination were analyzed for their reactivity against a panel of 29 viral structural proteins. The sera of pigs from the LAV group exhibited a strong antibody reactivity against various viral structural proteins, while the sera of pigs in the KV group only displayed weak antibody reactivity against the inner envelope (p32, p54, p12). There was a negative correlation between the intensity of antibody reactivity against five ASFV antigens, namely p12, p14, p15, p32, and pD205R, and the viral DNA titers in the blood of animals after the challenge infection. Thus, antibody reactivities against these five antigens warrant further evaluation as potential indicators of vaccine-induced protection

A novel approach in crude enzyme laccase production and application in emerging contaminant bioremediation

Laccase enzyme from white-rot fungi is a potential biocatalyst for the oxidation of emerging contaminants (ECs), such as pesticides, pharmaceuticals and steroid hormones. This study aims to develop a three-step platform to treat ECs: (i) enzyme production, (ii) enzyme concentration and (iii) enzyme application. In the first step, solid culture and liquid culture were compared. The solid culture produced significantly more laccase than the liquid culture (447 vs. 74 μM/min after eight days), demonstrating that white rot fungi thrived on a solid medium. In the second step, the enzyme was concentrated 6.6 times using an ultrafiltration (UF) process, resulting in laccase activity of 2980 μM/min. No enzymatic loss due to filtration and membrane adsorption was observed, suggesting the feasibility of the UF membrane for enzyme concentration. In the third step, concentrated crude enzyme was applied in an enzymatic membrane reactor (EMR) to remove a diverse set of ECs (31 compounds in six groups). The EMR effectively removed of steroid hormones, phytoestrogen, ultraviolet (UV) filters and industrial chemical (above 90%). However, it had low removal of pesticides and pharmaceuticals

Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework

peer reviewedTo enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open RAN (O-RAN). So far, however, the applicability of O-RAN in controlling and optimizing RAN functions has not been widely investigated. In this paper, we jointly optimize the flow-split distribution, congestion control and scheduling (JFCS) to enable an intelligent traffic steering application in O-RAN. Combining tools from network utility maximization and stochastic optimization, we introduce a multi-layer optimization framework that provides fast convergence, long-term utility-optimality and significant delay reduction compared to the state-of-the-art and baseline RAN approaches. Our main contributions are three-fold: i ) we propose the novel JFCS framework to efficiently and adaptively direct traffic to appropriate radio units; ii ) we develop low-complexity algorithms based on the reinforcement learning, inner approximation and bisection search methods to effectively solve the JFCS problem in different time scales; and iii ) the rigorous theoretical performance results are analyzed to show that there exists a scaling factor to improve the tradeoff between delay and utility-optimization. Collectively, the insights in this work will open the door towards fully automated networks with enhanced control and flexibility. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms in terms of the convergence rate, long-term utility-optimality and delay reduction

Assessment of the Effectiveness of Ich Tam Khang as a Supportive Therapy for Chronic Heart Failure

Background: Heart failure is a chronic disease needing lifelong management. Despite the advances that have been made in the treatment of the disease, both the longevity and quality of life for those with chronic heart failure remain impaired. A more effective therapeutic approach with less negative side effects is still needed. In this study, we evaluate Ich Tam Khang (ITK), the poly-ingredient herbal and nutritional preparation with multiple physiological actions, as a supportive therapy for patients with chronic heart failure.Aims of Study: To evaluate the effectiveness and safety of Ich Tam Khang as an adjunctive treatment of chronic heart failure.Methods: A total of 60 patients with chronic congestive heart failure were enrolled in this open label, cross-sectional and prospective study. All patients were treated with a conventional regimen (digoxin, diuretics, angiotensin-converting-enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs), beta blockers) for at least 4 weeks before being divided into two equal groups. In the treated patients with ITK, patients received conventional therapy plus 4 tablets ITK per day added in two divided doses. In the control patients, all patients kept the same conventional regimen without ITK. All patients were followed up for 3 months for clinical and para-clinical outcomes.Result: The symptoms of heart failure (dyspnea, palpitation, peripheral edema, neck vein distention, heptojugular reflex) decreased. Heart rate and blood pressure stabilized during treatment in the treated patients with ITK. Additionally, total cholesterol and HDL-cholesterol normalized in the patients treated with ITK. Most of echocardiography parameters in the ITK treated patients were superior to the control patients. ITK is safe and it has no side effects.Conclusion: ITK as a combination of herbal and nutritional preparation is effective in reducing heart failure symptoms, improving patient's quality of life for the patients with decompensated heart failure and reducing total cholesterol and LDL-C

Deep Learning-Based Detector for OFDM-IM

This letter presents the first attempt of exploiting deep learning (DL) in the signal detection of orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. Particularly, we propose a novel DL-based detector termed as DeepIM, which employs a deep neural network with fully connected layers to recover data bits in an OFDM-IM system. To enhance the performance of DeepIM, the received signal and channel vectors are pre-processed based on the domain knowledge before entering the network. Using datasets collected by simulations, DeepIM is first trained offline to minimize the bit error rate (BER) and then the trained model is deployed for the online signal detection of OFDM-IM. Simulation results show that DeepIM can achieve a near-optimal BER with a lower runtime than existing hand-crafted detectors

<i>Herschel</i> observations of B1-bS and B1-bN: two first hydrostatic core candidates in the Perseus star-forming cloud

We report far-infrared Herschel observations obtained between 70 μm and 500 μm of two star-forming dusty condensations, [HKM99] B1-bS and [HKM99] B1-bN, in the B1 region of the Perseus star-forming cloud. In the western part of the Perseus cloud, B1-bS is the only source detected in all six PACS and SPIRE photometric bands, but it is not visible in the Spitzer map at 24 μm. B1-bN is clearly detected between 100 μm and 250 μm. We have fitted the spectral energy distributions of these sources to derive their physical properties, and find that a simple greybody model fails to reproduce the observed spectral energy distributions. At least a two-component model is required, consisting of a central source surrounded by a dusty envelope. The properties derived from the fit, however, suggest that the central source is not a Class 0 object. We then conclude that while B1-bS and B1-bN appear to be more evolved than a pre-stellar core, the best-fit models suggest that their central objects are younger than a Class 0 source. Hence, they may be good candidates to be examples of the first hydrostatic core phase. The projected distance between B1-bS and B1-bN is a few Jeans lengths. If their physical separation is close to this value, this pair would allow studying the mutual interactions between two forming stars at a very early stage of their evolution

The spine of the swan: A Herschel study of the DR21 ridge and filaments in Cygnus X

In order to characterise the cloud structures responsible for the formation of high-mass stars, we present Herschel observations of the DR21 environment. Maps of the column density and dust temperature unveil the structure of the DR21 ridge and several connected filaments. The ridge has column densities larger than 1e23/cm^2 over a region of 2.3 pc^2. It shows substructured column density profiles and branching into two major filaments in the north. The masses in the studied filaments range between 130 and 1400 Msun whereas the mass in the ridge is 15000 Msun. The accretion of these filaments onto the DR21 ridge, suggested by a previous molecular line study, could provide a continuous mass inflow to the ridge. In contrast to the striations seen in e.g., the Taurus region, these filaments are gravitationally unstable and form cores and protostars. These cores formed in the filaments potentially fall into the ridge. Both inflow and collisions of cores could be important to drive the observed high-mass star formation. The evolutionary gradient of star formation running from DR21 in the south to the northern branching is traced by decreasing dust temperature. This evolution and the ridge structure can be explained by two main filamentary components of the ridge that merged first in the south.Comment: 8 pages, 5 figures, accepted for publication as a Letter in Astronomy and Astrophysic

Cluster-formation in the Rosette molecular cloud at the junctions of filaments

For many years feedback processes generated by OB-stars in molecular clouds, including expanding ionization fronts, stellar winds, or UV-radiation, have been proposed to trigger subsequent star formation. However, hydrodynamic models including radiation and gravity show that UV-illumination has little or no impact on the global dynamical evolution of the cloud. The Rosette molecular cloud, irradiated by the NGC2244 cluster, is a template region for triggered star-formation, and we investigated its spatial and density structure by applying a curvelet analysis, a filament-tracing algorithm (DisPerSE), and probability density functions (PDFs) on Herschel column density maps, obtained within the HOBYS key program. The analysis reveals not only the filamentary structure of the cloud but also that all known infrared clusters except one lie at junctions of filaments, as predicted by turbulence simulations. The PDFs of sub-regions in the cloud show systematic differences. The two UV-exposed regions have a double-peaked PDF we interprete as caused by shock compression. The deviations of the PDF from the log-normal shape typically associated with low- and high-mass star-forming regions at Av~3-4m and 8-10m, respectively, are found here within the very same cloud. This shows that there is no fundamental difference in the density structure of low- and high-mass star-forming regions. We conclude that star-formation in Rosette - and probably in high-mass star-forming clouds in general - is not globally triggered by the impact of UV-radiation. Moreover, star formation takes place in filaments that arose from the primordial turbulent structure built up during the formation of the cloud. Clusters form at filament mergers, but star formation can be locally induced in the direct interaction zone between an expanding HII--region and the molecular cloud.Comment: A&A Letter, in pres