In the last decade, artificial intelligence (AI) techniques have been extensively used for maximum power point tracking (MPPT) in the solar power system. This is because conventional MPPT techniques ...are incapable of tracking the global maximum power point (GMPP) under partial shading condition (PSC). The output curve of the power versus voltage for a solar panel has only one GMPP and multiple local maximum power points (MPPs). The integration of AI in MPPT is crucial to guarantee the tracking of GMPP while increasing the overall efficiency and performance of MPPT. The selection of AI-based MPPT techniques is complicated because each technique has its own merits and demerits. In general, all of the AI-based MPPT techniques exhibit fast convergence speed, less steady-state oscillation and high efficiency, compared with the conventional MPPT techniques. However, the AI-based MPPT techniques are computationally intensive and costly to realize. Overall, the hybrid MPPT is favorable in terms of the balance between performance and complexity, and it combines the advantages of conventional and AI-based MPPT techniques. In this paper, a detailed comparison of classification and performance between 6 major AI-based MPPT techniques have been made based on the review and MATLAB/Simulink simulation results. The merits, open issues and technical implementations of AI-based MPPT techniques are evaluated. We intend to provide new insights into the choice of optimal AI-based MPPT techniques.
adenosine nucleoside inhibitor of dengue virus Yin, Zheng; Chen, Yen-Liang; Schul, Wouter ...
Proceedings of the National Academy of Sciences - PNAS,
12/2009, Letnik:
106, Številka:
48
Journal Article
Recenzirano
Odprti dostop
Dengue virus (DENV), a mosquito-borne flavivirus, is a major public health threat. The virus poses risk to 2.5 billion people worldwide and causes 50 to 100 million human infections each year. ...Neither a vaccine nor an antiviral therapy is currently available for prevention and treatment of DENV infection. Here, we report a previously undescribed adenosine analog, NITD008, that potently inhibits DENV both in vitro and in vivo. In addition to the 4 serotypes of DENV, NITD008 inhibits other flaviviruses, including West Nile virus, yellow fever virus, and Powassan virus. The compound also suppresses hepatitis C virus, but it does not inhibit nonflaviviruses, such as Western equine encephalitis virus and vesicular stomatitis virus. A triphosphate form of NITD008 directly inhibits the RNA-dependent RNA polymerase activity of DENV, indicating that the compound functions as a chain terminator during viral RNA synthesis. NITD008 has good in vivo pharmacokinetic properties and is biologically available through oral administration. Treatment of DENV-infected mice with NITD008 suppressed peak viremia, reduced cytokine elevation, and completely prevented the infected mice from death. No observed adverse effect level (NOAEL) was achieved when rats were orally dosed with NITD008 at 50 mg/kg daily for 1 week. However, NOAEL could not be accomplished when rats and dogs were dosed daily for 2 weeks. Nevertheless, our results have proved the concept that a nucleoside inhibitor could be developed for potential treatment of flavivirus infections.
Green transportation has been increasingly gaining attention in recent years. Existing pheromone-based traffic management frameworks were developed to reduce urban congestion by fusing traffic lights ...control strategies and vehicle routing schemes. Despite a significant reduction in traffic congestions, the greener aspects of transportation were not well investigated. In view of this, a Pheromone-based Green Transportation System (PGTS) is proposed to reduce Greenhouse Gas emissions and urban congestion in a three-step approach. First, traffic congestions are predicted based on the transport pheromone intensity of the target and adjacent upstream roads through an online epsilon-Support Vector Regression model. Second, a Coordinated Traffic Light Control (CTLC) strategy generates green wave scenario, dispersing heavy traffic on congested roads to the coordinated downstream paths. Third, a Cooperative Green Vehicle Routing (CGVR) takes a further leap by probabilistically rerouting upstream vehicles from entering the congested road, preventing the accumulation of vehicles that can lead to upstream congestion. Intuitively, the integration of CTLC and CGVR increases the chances that vehicles traversing multiple intersections with fewer frequencies of acceleration, effectively marking down fuel consumption. The proposed PGTS can be realized through a Pheromone-based Hierarchical Multi-Agent System (PHMAS). Based on Singapore traffic data, experimental results from a microscopic simulation SUMO show that the proposed PGTS outperforms other six approaches in reducing carbon dioxide emissions by 37.7%, fuel consumption by 37.6%, mean travel time by 47.5%, mean waiting time by 57.3%, and increasing number of arrived vehicles at designated destinations by 62.6%.
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•Green transportation was not well explored in existing pheromone framework.•Pheromone-based Green Transportation System (PGTS) is proposed to reduce emissions.•PGTS integrates coordinated traffic lights and cooperative green vehicle routing.•This integration disperses upstream and downstream traffic to reduce fuel burnt.•Vehicles can traverse intersections with fewer frequencies of acceleration in PGTS.
•Traffic Simulation that models live traffic.•Traffic congestion prediction using neural network.•Missing data imputation using historically weighted averages.•Vehicle rerouting system that is robust ...to missing data is developed.
A robust traffic rerouting system is important in traffic management, alongside an accurate traffic simulation model. However, missing data continues to be a problem as it will inevitably cause errors in predicting the congestion levels, resulting in a less efficient rerouting. The lack of a realistic traffic simulation also serves to hamper the development of a better traffic management system. As such, this paper aims to address both problems by proposing three solutions: (i) a traffic simulation that would model a live-traffic, (ii) a pheromone-based, neural network traffic prediction and rerouting system, and (iii) a missing data handling method utilising weighted historical data method named Weighted Missing Data Imputation (WEMDI). The traffic simulation model was benchmarked using Google Maps rerouting system. WEMDI was tested by comparing the performance of the rerouting system with and without WEMDI’s integration for various levels of missing data. The results showed that the traffic simulation model displayed a high correlation to that of Google Maps, and the WEMDI-integrated system displayed 38% to 44% improvement in the related traffic factors, when compared to a situation with no rerouting system in place, and up to 19.39% increase in performance compared to the base rerouting system for missing data levels of 50%. The WEMDI system also displayed robustness in routing other locations, displaying a similarly high performance.
Abstract We performed a focused siRNA screen in an A549 dengue type 2 New Guinea C subgenomic replicon cell line (Rluc-replicon) that contains a Renilla luciferase cassette. We found that siRNA ...mediated knock down of mevalonate diphospho decarboxylase (MVD) inhibited viral replication of the Rluc-replicon and DEN-2 NGC live virus replication in A549 cells. When the Rluc-replicon A459 cells were grown in delipidated media the replicon expression was suppressed and MVD knock down could further sensitize Renilla expression. Hymeglusin and zaragozic acid A could inhibit DEN-2 NGC live virus replication in K562 cells, while lovastatin could inhibit DEN-2 NGC live virus replication in human peripheral blood mononuclear cells. Renilla expression could be rescued in fluvastatin treated A549 Rluc-replicon cells after the addition of mevalonate, and partially restored with geranylgeranyl pyrophosphate, or farnesyl pyrophosphate. Our data suggest genetic and pharmacological modulation of cholesterol biosynthesis can regulate dengue virus replication.
This study paper presents a comprehensive review of virtual inertia (VI)-based inverters in modern power systems. The transition from the synchronous generator (SG)-based conventional power ...generation to converter-based renewable energy sources (RES) deteriorates the frequency stability of the power system due to the intermittency of wind and photovoltaic (PV) generation. Unlike conventional power generation, the lack of rotational inertia becomes the main challenge to interface RES with the electrical grid via power electronic converters. In the past several years, researchers have addressed this issue by emulating the behavior of SG mathematically via pulse width modulation (PWM) controller linked to conventional inverter systems. These systems are technically known as VI-based inverters, which consist of virtual synchronous machine (VSM), virtual synchronous generator (VSG), and synchronverter. This paper provides an extensive insight into the latest development, application, challenges, and prospect of VI application, which is crucial for the transition to low-carbon power system.
Mammalian genomes are viewed as functional organizations that orchestrate spatial and temporal gene regulation. CTCF, the most characterized insulator-binding protein, has been implicated as a key ...genome organizer. However, little is known about CTCF-associated higher-order chromatin structures at a global scale. Here we applied chromatin interaction analysis by paired-end tag (ChIA-PET) sequencing to elucidate the CTCF-chromatin interactome in pluripotent cells. From this analysis, we identified 1,480 cis- and 336 trans-interacting loci with high reproducibility and precision. Associating these chromatin interaction loci with their underlying epigenetic states, promoter activities, enhancer binding and nuclear lamina occupancy, we uncovered five distinct chromatin domains that suggest potential new models of CTCF function in chromatin organization and transcriptional control. Specifically, CTCF interactions demarcate chromatin-nuclear membrane attachments and influence proper gene expression through extensive cross-talk between promoters and regulatory elements. This highly complex nuclear organization offers insights toward the unifying principles that govern genome plasticity and function.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
•A novel adaptive virtual inertia control strategy (VICS) for synchronverter has been designed.•It is to stabilize the frequency of grid-connected solar power system under dynamic weather.•Fault-ride ...through (FRT) capabilities are also validated to ensure continuous operation.
As the grid-connected solar power system grows rapidly, virtual inertia control strategy (VICS) becomes crucial to enable stable grid integration. However, the existing VICS is lack of dynamic weather analysis with maximum power point tracking (MPPT) and fault-ride through (FRT) capabilities such as low voltage ride through (LVRT) and high voltage ride-through (HVRT). In this paper, the proposed adaptive VICS with variable moment of inertia (J) and damping factor (DP) demonstrates its effectiveness with faster frequency recovery, less overshooting and continuous stable operation under grid fault and dynamic weather. Case studies have been conducted in MATLAB®/Simulink simulation to demonstrate the feasibility of the proposed VICS. The frequency nadir has been improved by at least +0.95 Hz (+1.9%) compared to the conventional inverter and PI-based synchronverter. The simulation results are validated and verified by the emulated hardware based on Typhoon® Hardware-In-Loop (HIL) 402 real-time simulation. Overall, the proposed VICS is able to operate in stable condition by regulating grid frequency (fg) and voltage (vg) under varying irradiance and temperature, voltage sag/surge, sudden load changes and overloading conditions.
Human-Object Interaction (HOI) detection recognizes how persons interact with objects, which is advantageous in autonomous systems such as self-driving vehicles and collaborative robots. However, ...current HOI detectors are often plagued by model inefficiency and unreliability when making a prediction, which consequently limits its potential for real-world scenarios. In this paper, we address these challenges by proposing ERNet, an end-to-end trainable convolutional-transformer network for HOI detection. The proposed model employs an efficient multi-scale deformable attention to effectively capture vital HOI features. We also put forward a novel detection attention module to adaptively generate semantically rich instance and interaction tokens. These tokens undergo pre-emptive detections to produce initial region and vector proposals that also serve as queries which enhances the feature refinement process in the transformer decoders. Several impactful enhancements are also applied to improve the HOI representation learning. Additionally, we utilize a predictive uncertainty estimation framework in the instance and interaction classification heads to quantify the uncertainty behind each prediction. By doing so, we can accurately and reliably predict HOIs even under challenging scenarios. Experiment results on the HICO-Det, V-COCO, and HOI-A datasets demonstrate that the proposed model achieves state-of-the-art performance in detection accuracy and training efficiency. Codes are publicly available at https://github.com/Monash-CyPhi-AI-Research-Lab/ernet .
Radiation therapy (RT) continues to be a cornerstone in the treatment for many cancers. Unfortunately, not all individuals respond effectively to RT resulting clinically in two groups consisting of ...nonresponders (progressive disease) and responders (tumor control/cure). The mechanisms that govern the outcome of radiotherapy are poorly understood. Interestingly, a new paradigm has emerged demonstrating that the immune system mediates many of the antitumor effects of RT. Therefore, we hypothesized that the immune response following RT may dictate the efficacy of treatment. To examine this, we developed a tumor model that mirrors this clinically relevant phenomenon in which mice bearing Colon38, a colon adenocarcinoma, were treated locally with 15Gy RT resulting in both nonresponders and responders. More importantly, we were able to distinguish responders from nonresponders as early as 4 days post‐RT allowing for the unique opportunity to identify critical events that ultimately determined the effectiveness of therapy. Intratumoral immune cells and interferon‐gamma were increased in responsive tumors and licensed CD8 T cells to exhibit lytic activity against tumor cells, a response that was diminished in tumors refractory to RT. Combinatorial treatment with RT and the immunomodulatory cytokine IL‐12 resulted in complete remission of cancer in 100% of cases compared to a cure rate of only 12% with RT alone. Similar data were obtained when IL‐12 was delivered by microspheres. Therefore, the efficacy of RT may depend on the strength of the immune response induced after radiotherapy. Additionally, immunotherapy that further stimulates the immune cells may enhance the effectiveness of RT.
What's new?
The immune system may play an important role in radiation therapy (RT). In this study, the authors developed a novel murine‐tumor model in order to study the events that follow RT. They found that ‘responders’ exhibited increased intratumoral immune responses. When RT was then combined with IL‐12, 100% of tumors responded (vs. a cure rate of only 12% with RT alone). This suggests that the immune response elicited by radiation therapy (RT) may be as important as the radiation itself in successful treatment, and that immunomodulatory cytokines may enhance the effectiveness of RT.
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