This paper addresses a two-stage framework for the economic operation of a microgrid-like electric vehicle (EV) parking deck with on-site renewable energy generation (roof-top photovoltaic panel). ...This microgrid-like EV parking deck is a localized grouping of distributed generation (solar), energy storage (EV batteries), and load (EV charging load). Although EV parking decks can enable greater adoption of renewable energy sources by scheduling charging loads to coincide with periods of strong sun, the inherent intermittency of renewable energy resources and variable EV parking behaviors complicates the economic operation. In this paper, the proposed first stage of this framework provides the parking deck operators with a stochastic approach for dealing with the uncertainty of solar energy so as to make an optimal price decision (marginal electricity sale price and parking fee rebate) at the day-ahead time scale. The second stage introduces a model predictive control-based operation strategy of EV charging dealing with the uncertainty of parking behaviors within the real-time operation. Case studies demonstrate the better performance of the proposed framework, offering an effective day-ahead marginal electricity price for tomorrow's operation and increasing the microgrid-like EV parking deck's revenue during the real-time operation.
To explore the effect of image-guided systems in phacoemulsification with intraocular lens (IOL) implantation.
We searched Pubmed, Embase and China National Knowledge Infrastructure (inception to ...January 20, 2021). Two researchers extracted data and assessed paper quality independently. Uncorrected distance visual acuity (UDVA) before and after surgery, best corrected visual acuity (BCVA) before and after surgery, preoperative cylinder, postoperative residual refractive cylinder, postoperative corneal cylinder, IOL misalignment, and intraocular pressure (IOP) were compared.
We included 14 studies with 885 cataract eyes. All data were performed using Review Manager 5.3 (RevMan 5.3) (
https://revman.cochrane.org/
). Cases of all preoperative outcomes showed no significant difference between image-guided group and manual group. There was no significant difference in postoperative UDVA (Standard mean difference (SMD: −0.11, 95% CI: −0.32 to 0.11, I
2
= 59%, p = 0.33)), BCVA (SMD: 0.03, 95% CI: −0.12 to 0.18, I
2
= 36%, p = 0.72), corneal cylinder (Weighted mean difference WMD: 0.13, 95% CI: −0.06 to −0.32, I
2
= 0%, p = 0.17), IOP (WMD: −0.37, 95% CI: −1.36 to −0.62, I
2
= 9%, p = 0.46) between two groups. There was less residual refractive cylinder in image-guided group than in manual group (WMD: −0.20, 95% CI: −0.26 to −0.14, I
2
= 59%, p＜0.00001). It is more accurate in IOL alignment when combined with image-guided systems (WMD: −1.20, 95% CI: −1.43 to −0.96, I
2
= 14%, p < 0.00001).
Image-guided systems can improve the effect in phacoemulsification with intraocular lens (IOL) implantation.
Overcoming the multidrug-resistant (MDR) bacterial infection is a challenge and urgently needed in wound healing. Few wound dressings possess the capacity to treat MDR bacterial infections and ...enhance wound healing. Herein, we develop an elastomeric, photoluminescent, and antibacterial hybrid polypeptide-based nanofibrous matrix as a multifunctional platform to inhibit the MDR bacteria and enhance wound healing. The hybrid nanofibrous matrix was composed of poly(citrate)-ε-poly lysine (PCE) and poly caprolactone (PCL). The PCL–PCE hybrid nanofibrous matrix showed a biomimetic elastomeric behavior, robust antibacterial activity including killing MDR bacteria capacity, and excellent biocompatibility. PCL–PCE nanofibrous system can efficiently prevent the MDR bacteria-derived wound infection and significantly enhance the complete skin-thickness wound healing and skin regeneration in a mouse model. PCL–PCE hybrid nanofibrous matrix might become a competitive multifunctional dressing for bacteria-infected wound healing and skin regeneration.
The large and catastrophic wildfires have been increasing across the globe in the recent decade, highlighting the importance of simulating and forecasting fire dynamics in near real-time. This is ...extremely challenging due to the complexities of physical models and geographical features. Running physics-based simulations for large wildfire events in near real-time are computationally expensive, if not infeasible. In this work, we develop and test a novel data-model integration scheme for fire progression forecasting, that combines Reduced-order modelling, recurrent neural networks (Long-Short-Term Memory), data assimilation, and error covariance tuning. The Reduced-order modelling and the machine learning surrogate model ensure the efficiency of the proposed approach while the data assimilation enables the system to adjust the simulation with observations. We applied this algorithm to simulate and forecast three recent large wildfire events in California from 2017 to 2020. The deep-learning-based surrogate model runs around 1000 times faster than the Cellular Automata simulation which is used to generate training data-sets. The daily fire perimeters derived from satellite observation are used as observation data in Latent Assimilation to adjust the fire forecasting in near real-time. An error covariance tuning algorithm is also performed in the reduced space to estimate prior simulation and observation errors. The evolution of the averaged relative root mean square error (R-RMSE) shows that data assimilation and covariance tuning reduce the RMSE by about 50% and considerably improves the forecasting accuracy. As a first attempt at a reduced order wildfire spread forecasting, our exploratory work showed the potential of data-driven machine learning models to speed up fire forecasting for various applications.
•We are the first to train ML surrogate models for dynamical fire diffusion problems with a stochastic simulation code.•We combine ROM, RNN, DA and error covariance tuning for real-time wildfire nowcasting coupled with satellite observations.•The proposed surrogate model is thousands of times faster than either Cellular Automata or CFD-based simulations.•We prove why the DI01 cov-tuning diverges when the background and observation matrices have the same correlation structure.•The algorithm scheme proposed in this work can be easily applied/extended to other dynamical systems.
Obesity is a leading contributor to numerous diseases, such as diabetes mellitus, cardiovascular diseases, and cancers. Therefore, seeking effective and safe approaches to control obesity is ...essential. Gut microbiota has been demonstrated to play a critical role in the occurrence of obesity via the regulation of energy metabolism. The composition and abundance of gut microbiota can be altered by the diet. Recently, many dietary plants have been demonstrated to exert anti-obesity effects through bioactive components that modulate gut microbiota, which has drawn increasing research attention.
In this review, the obesity-associated gut microbiota has been summarized and classified into obesogenic and anti-obesity categories. Subsequently, some anti-obesity dietary plants with gut microbiota-modulating activities and the mechanisms of action of their bioactive components are discussed.
The effects of gut microbiota on obesity have been found in most animal and some human studies. Certain strains of Firmicutes, Lactobacillus, and Bacteroidetes are positively associated with obesity development, while Bifidobacterium, most Lactobacillus, and some Bacteroidetes show anti-obesity activities. Some dietary plants, such as grapes, berries, apple, turmeric, chili, soy, sorghum, and barley, show anti-obesity efficacy through increasing the diversity of gut microbiota, up-regulating anti-obesity gut microbiota and down-regulating obesogenic gut microbiota.
This review may stimulate further development of functional foods to treat obesity through modulating gut microbiota. Future work will rely on the exploration of more dietary plants and their components with anti-obesity and gut microbiota-modulating effects, and further investigation of related mechanisms as well as clinical trials.
•The obesogenic and anti-obesogenic gut microbiota are summarized.•The effects of anti-obesity dietary plants on gut microbiota are discussed.•Mechanisms of dietary plants on gut microbiota regulation are highlighted.•Gut microbiota is a promising target to develop anti-obesity functional foods.
The usage of zerovalent iron (ZVI) activated persulfate to induce sulfate radical (SO4 −·) oxidation of both aqueous and solid phase naphthalene (Nap) was investigated. It was determined that the ...removal of Nap particles occurred through an indirect route. Specifically, Nap released through dissolution from the pure Nap particles was subsequently oxidized in the aqueous phase by SO4 −·. Rapid destruction of dissolved Nap created a greater concentration gradient between the solid and aqueous phases. This caused more Nap particles to be dissolved which were then available for the subsequent oxidative destruction of dissolved Nap. The rate constant (k obs,Nap) of ZVI activated persulfate degradation of dissolved Nap was determined to be 3.74 min−1. The overall dissolution mass transfer coefficients (k La) for the Nap particles were determined, 3.0 × 10−2 min−1 with initial 10 mg Nap in 40 mL water, and found to be proportional to the quantities of the Nap particles present. The results indicate that the k obs,Nap is much greater than the k La. The net result of the dissolution of Nap particles and the destruction of dissolved Nap by oxidation was the removal of Nap particles. Sequential additions of ZVI at a lower concentration to slow down the formation of SO4 −· can prevent the scavenging of SO4 −· by ZVI and enhance the removal of Nap particles. The results of the mass balance analysis during the oxidized, aqueous and solid phases of Nap were consistent with experimental observations.
In the field of monitored quantum circuits, it has remained an open question whether finite-time protocols for preparing long-range entangled states lead to phases of matter that are stable to gate ...imperfections, that can convert projective into weak measurements. Here, we show that in certain cases, long-range entanglement persists in the presence of weak measurements, and gives rise to novel forms of quantum criticality. We demonstrate this explicitly for preparing the two-dimensional Greenberger-Horne-Zeilinger cat state and the three-dimensional toric code as minimal instances. In contrast to random monitored circuits, our circuit of gates and measurements is deterministic; the only randomness is in the measurement outcomes. We show how the randomness in these weak measurements allows us to track the solvable Nishimori line of the random-bond Ising model, rigorously establishing the stability of the glassy long-range entangled states in two and three spatial dimensions. Away from this exactly solvable construction, we use hybrid tensor network and Monte Carlo simulations to obtain a nonzero Edwards-Anderson order parameter as an indicator of long-range entanglement in the two-dimensional scenario. We argue that our protocol admits a natural implementation in existing quantum computing architectures, requiring only a depth-3 circuit on IBM's heavy-hexagon transmon chips.
The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients result in insufficient spectrum resources ...and communication overload. Mobile Edge Computing (MEC) enabled 5G health monitoring is conceived as a favorable paradigm to tackle such an obstacle. In this paper, we construct a cost-efficient in-home health monitoring system for IoMT by dividing it into two sub-networks, i.e., intra-Wireless Body Area Networks (WBANs) and beyond-WBANs. Highlighting the characteristics of IoMT, the cost of patients depends on medical criticality, Age of Information (AoI) and energy consumption. For intra-WBANs, a cooperative game is formulated to allocate the wireless channel resources. While for beyond-WBANs, considering the individual rationality and potential selfishness, a decentralized non-cooperative game is proposed to minimize the system-wide cost in IoMT. We prove that the proposed algorithm can reach a Nash equilibrium. In addition, the upper bound of the algorithm time complexity and the number of patients benefiting from MEC is theoretically derived. Performance evaluations demonstrate the effectiveness of our proposed algorithm with respect to the system-wide cost and the number of patients benefiting from MEC.
Cardiovascular diseases (CVDs) are leading global health problems. Accumulating epidemiological studies have indicated that consuming fruits was inversely related to the risk of CVDs. Moreover, ...substantial experimental studies have supported the protective role of fruits against CVDs, and several fruits (grape, blueberry, pomegranate, apple, hawthorn, and avocado) have been widely studied and have shown potent cardiovascular protective action. Fruits can prevent CVDs or facilitate the restoration of morphology and functions of heart and vessels after injury. The involved mechanisms included protecting vascular endothelial function, regulating lipids metabolism, modulating blood pressure, inhibiting platelets function, alleviating ischemia/reperfusion injury, suppressing thrombosis, reducing oxidative stress, and attenuating inflammation. The present review summarizes recent discoveries about the effects of fruits on CVDs and discusses potential mechanisms of actions based on evidence from epidemiological, experimental, and clinical studies.
With the booming development of medical informatization and the ubiquitous connections in the fifth generation mobile communication technology (5G) era, the heterogeneity and explosive growth of ...medical data have brought huge challenges to data access, security and privacy, as well as information processing in Internet of Medical Things (IoMT). This article provides a comprehensive review of how to realize the timely processing and analysis of medical big data and the sinking of high-quality medical resources under the constraints of the existing medical environment and medical-related equipment. We mainly focus on the advantages brought by the cloud computing, edge computing and artificial intelligence technologies to the IoMT. We also explore how to rationalize the use of medical resources and the security and privacy of medical data, so that high-quality medical services can be provided to patients. Finally, we discuss the current challenges and possible future research directions in the edge-cloud computing and artificial intelligence related IoMT.
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