187 research outputs found
QoS-Aware Utility-Based Resource Allocation in Mixed-Traffic Multi-User OFDM Systems
This paper deals with the joint subcarrier and power allocation problem in a downlink multi-user orthogonal frequency division multiplexing system subject to user delay and minimum rate quality-of-service (QoS) requirements over a frequency-selective multi-carrier fading channel. We aim to maximize the utility-pricing function, formulated as the difference between the achieved spectral efficiency and the associated linear cost function of transmit power scaled by a system-dependent parameter. For a homogeneous system, we show that the joint resource allocation can be broken down into sequential problems while retaining the optimality. Specifically, the optimal solution is obtained by first assigning each subcarrier to the user with the best channel gain. Subsequently, the transmit power for each subcarrier is adapted according to water-filling policy if the global optimum is feasible, else it is given by a nonwater-filling power adaptation. For a heterogeneous system, an optimal solution needs exhaustive search and hence, we resort to two reduced-complexity sub-optimal algorithms. Algorithm-I is a simple extension of the aforementioned optimal algorithm developed for a homogeneous system, while Algorithm-II further takes into consideration the heterogeneity in user QoS requirements for performance enhancement. Simulation results reveal the impacts of user QoS requirements, number of subcarriers and number of users on the system transmit power
Scanning SQUID microscopy of vortex clusters in multiband superconductors
In type-1.5 superconductors, vortices emerge in clusters, which grow in size
with increasing magnetic field. These novel vortex clusters and their field
dependence are directly visualized by scanning SQUID microscopy at very low
vortex densities in MgB2 single crystals. Our observations are elucidated by
simulations based on a two-gap Ginzburg-Landau theory in the type-1.5 regime.Comment: 4 pages, 5 figures, to be published in Physical Review
Multi-Agent Reinforcement Learning for Joint Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems
We consider the problem of joint channel assignment and power allocation in
underlaid cellular vehicular-to-everything (C-V2X) systems where multiple
vehicle-to-infrastructure (V2I) uplinks share the time-frequency resources with
multiple vehicle-to-vehicle (V2V) platoons that enable groups of connected and
autonomous vehicles to travel closely together. Due to the nature of fast
channel variant in vehicular environment, traditional centralized optimization
approach relying on global channel information might not be viable in C-V2X
systems with large number of users. Utilizing a reinforcement learning (RL)
approach, we propose a distributed resource allocation (RA) algorithm to
overcome this challenge. Specifically, we model the RA problem as a multi-agent
system. Based solely on the local channel information, each platoon leader, who
acts as an agent, collectively interacts with each other and accordingly
selects the optimal combination of sub-band and power level to transmit its
signals. Toward this end, we utilize the double deep Q-learning algorithm to
jointly train the agents under the objectives of simultaneously maximizing the
V2I sum-rate and satisfying the packet delivery probability of each V2V link in
a desired latency limitation. Simulation results show that our proposed
RL-based algorithm achieves a close performance compared to that of the
well-known exhaustive search algorithm.Comment: 6 pages, 4 figure
VLSP SHARED TASK: SENTIMENT ANALYSIS
Sentiment analysis is a natural language processing (NLP) task of identifying orextracting the sentiment content of a text unit. This task has become an active research topic since the early 2000s. During the two last editions of the VLSP workshop series, the shared task on Sentiment Analysis (SA) for Vietnamese has been organized in order to provide an objective evaluation measurement about the performance (quality) of sentiment analysis tools, and encouragethe development of Vietnamese sentiment analysis systems, as well as to provide benchmark datasets for this task. The rst campaign in 2016 only focused on the sentiment polarity classication, with a dataset containing reviews of electronic products. The second campaign in 2018 addressed the problem of Aspect Based Sentiment Analysis (ABSA) for Vietnamese, by providing two datasets containing reviews in restaurant and hotel domains. These data are accessible for research purpose via the VLSP website vlsp.org.vn/resources. This paper describes the built datasets as well as the evaluation results of the systems participating to these campaigns
Prospectus, September 6, 1990
https://spark.parkland.edu/prospectus_1990/1019/thumbnail.jp
Prospectus, August 1988
https://spark.parkland.edu/prospectus_1988/1000/thumbnail.jp
The effects of free trade agreements on the stock market: Evidence from Vietnam.
This study examines the effects of news events related to the European Union-Vietnam Free Trade Agreement (EVFTA) on the Vietnam stock market from 2010 to 2020. We calculate sectoral abnormal returns prior to, during, and after announcements and find that the Vietnamese stock market is susceptible to these events. We discovered that the announcement had a negative impact on the market, which might diminish the effectiveness of the Agreement. The findings show that more than half of Vietnam's sectors had an immediate reaction to EVFTA announcements, with fourteen reacting negatively and six responding positively. Two of the ten events did not have any immediate impact on these industries but all events resulted in either early or delayed reactions. We also find market scepticism and major changes in the deal led to the emergence of a diamond risk structure. We run multiple robustness tests to account for market integration and other factors that may affect stock returns. In addition, we explore potential sectoral systematic risk changes following these occurrences using different ARCH-type models. These additional tests confirm the robustness of our findings
Point-of-care C-reactive protein testing to reduce inappropriate use of antibiotics for non-severe acute respiratory infections in Vietnamese primary health care: a randomised controlled trial
Background Inappropriate antibiotic use for acute respiratory tract infections is common in primary health care, but
distinguishing serious from self-limiting infections is diffi cult, particularly in low-resource settings. We assessed
whether C-reactive protein point-of-care testing can safely reduce antibiotic use in patients with non-severe acute
respiratory tract infections in Vietnam.
Method We did a multicentre open-label randomised controlled trial in ten primary health-care centres in northern
Vietnam. Patients aged 1–65 years with at least one focal and one systemic symptom of acute respiratory tract infection
were assigned 1:1 to receive either C-reactive protein point-of-care testing or routine care, following which antibiotic
prescribing decisions were made. Patients with severe acute respiratory tract infection were excluded. Enrolled
patients were reassessed on day 3, 4, or 5, and on day 14 a structured telephone interview was done blind to the
intervention. Randomised assignments were concealed from prescribers and patients but not masked as the test
result was used to assist treatment decisions. The primary outcome was antibiotic use within 14 days of follow-up. All
analyses were prespecifi ed in the protocol and the statistical analysis plan. All analyses were done on the intention-totreat
population and the analysis of the primary endpoint was repeated in the per-protocol population. This trial is
registered under number NCT01918579.
Findings Between March 17, 2014, and July 3, 2015, 2037 patients (1028 children and 1009 adults) were enrolled and
randomised. One adult patient withdrew immediately after randomisation. 1017 patients were assigned to receive
C-reactive protein point-of-care testing, and 1019 patients were assigned to receive routine care. 115 patients in the
C-reactive protein point-of-care group and 72 patients in the routine care group were excluded in the intention-to-treat
analysis due to missing primary endpoint. The number of patients who used antibiotics within 14 days was 581 (64%)
of 902 patients in the C-reactive protein group versus 738 (78%) of 947 patients in the control group (odds ratio
[OR] 0·49, 95% CI 0·40–0·61; p<0·0001). Highly signifi cant diff erences were seen in both children and adults, with
substantial heterogeneity of the intervention eff ect across the 10 sites (I²=84%, 95% CI 66–96). 140 patients in the
C-reactive protein group and 137 patients in the routine care group missed the urine test on day 3, 4, or 5. Antibiotic
activity in urine on day 3, 4, or 5 was found in 267 (30%) of 877 patients in the C-reactive protein group versus
314 (36%) of 882 patients in the routine treatment group (OR 0·78, 95% CI 0·63–0·95; p=0·015). Time to resolution
of symptoms was similar in both groups. Adverse events were rare, with no deaths and a total of 14 hospital admissions
(six in the C-reactive protein group and eight in the control group).
Interpretation C-reactive protein point-of-care testing reduced antibiotic use for non-severe acute respiratory tract
infection without compromising patients’ recovery in primary health care in Vietnam. Health-care providers might
have become familiar with the clinical picture of low C-reactive protein, leading to reduction in antibiotic prescribing
in both groups, but this would have led to a reduction in observed eff ect, rather than overestimation. Qualitative
analysis is needed to address diff erences in context in order to implement this strategy to improve rational antibiotic
use for patients with acute respiratory infection in low-income and middle-income countries
Heterologous expression and characterization of a MoAA16 polysaccharide monooxygenase from the rice blast fungus Magnaporthe oryzae
Background: Cellulose is an organic carbon source that can be used as a sustainable alternative for energy, materials, and chemicals. However, the substantial challenge of converting it into soluble sugars remains a major obstacle in its use as a biofuel and chemical feedstock. A new class of enzymes knowns as copper-dependent polysaccharide monooxygenases (PMOs) or lytic polysaccharide monooxygenases (LPMOs) can break down polysaccharides such as cellulose, chitin, and starch through oxidation. This process enhances the efficiency of cellulose degradation by cellulase. Results: The genome of the fungus Magnaporthe oryzae, the causal agent of rice blast disease, contains the MGG_00245 gene, which encodes a putative PMO referred to as MoAA16. MoAA16 has been found to be highly expressed in planta during the early stages of fungal infection. The gene was optimized for heterologous expression in Pichia pastoris, and its oxidative cleavage activity on cellulose was characterized by analyzing soluble oligosaccharide products using highperformance anion exchange chromatography (HPAEC-PAD). The reaction catalyzed by MoAA16 requires 2 electrons from an electron donor, such as ascorbic acid, and aerobic conditions. It primarily produces Glc1 to Glc4 oligosaccharides, as well as oxidized cellobionic and cellotrionic acids. MoAA16 has been observed to enhance cellulase hydrolysis on phosphoric acid swollen cellulose (PASC) substrate, resulting in the production of more monosaccharide products. Conclusions: Our findings reveal the successful heterologous expression of MoAA16 in P. pastoris and its cellulose-active PMO properties. These results highlight the potential of MoAA16 as a promising candidate for applications in biofuel production and chemical synthesis. How to cite: Nguyen HM, Le LQ, Sella L, et al. Heterologous expression and characterization of a MoAA16 polysaccharide monooxygenase from the rice blast fungus Magnaporthe oryzae. Electron J Biotechnol 2023. https://doi.org/10.1016/j.ejbt.2023.06.002
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