In power electronics systems, system design and operation often involve multiple time and space scales, ranging from nanosecond switching dynamics to hour-level system operation behavior. Due to the ...complexity of these systems and the rise of wide-gap semiconductor technology, a series of multi-scale phenomena have emerged that are difficult to ignore. The high frequency of switching operations makes multi-scale effects particularly significant, including the fast dynamic response of the power loop, EMI, and heat conduction problems. They are key factors that must be considered in the design to ensure the efficient and reliable operation of power electronic devices. This study proposes the construction and simulation of a joint scale model for power electronic converters based on wavelet decomposition and reconstruction algorithms to address the multi-scale phenomenon and limitations of single-scale power electronic converters. Firstly, a joint scale model for power electronic converters at both macro and micro-scales was established, targeting both single-scale models and simple combinations of multiple scale models for power electronic converters. The traditional single-scale model is sufficient to describe the average behavior of the converter, but it has serious limitations in capturing fast transient processes and high-frequency switching behavior in power electronic systems. These limitations often manifest themselves when there is a need to capture fine timescales of detail. By transforming between the time domain and the frequency domain, wavelet decomposition enables the model to capture both macroscopic average characteristics and microscopic transient dynamics. The wavelet reconstruction algorithm can simulate all kinds of fast changes in the actual working process more accurately and compress irrelevant information while retaining key signal features, so as to optimize the simulation performance of the model. Secondly, this algorithm is used to analyze BC in short time scale. Finally, the short time scale characteristics of power electronic converters are analyzed. Experimental results show that the fusion of wavelet decomposition and reconstruction algorithm enhances the accuracy of the power electronic converter model and improves the performance of the system. The model achieves an error reduction of nearly 3% in the calculation step size of 10-7s, which has a significant impact on the high precision requirements of high-frequency operations. In addition, the optimal calculation step size of 8×10-8s achieves an error reduction of more than 14%, making an important contribution to the transient analysis and fine structure simulation. The wavelet algorithm can improve the accuracy of multi-scale modeling in power electronic system and reduce the simulation time. The reduction of error not only shows the improvement of the accuracy of the model, but also shows its practical significance in the design and test of the actual power electronic system. The reduction in error reveals the ability to more accurately predict and mitigate potential performance problems in matching tests with actual hardware, as well as its ability to adapt to emerging wide bandgap semiconductor materials and structures.
•Two recommendation models were proposed for cold start items.•The models combine time-aware collaborative filtering and deep learning.•Experiment on Netflix dataset showed large improvement over ...existing approaches.
Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.
•We developed a framework to evaluate the impactsof different LUCC scenarios on habitat quality with low data demand.•We further advance the InVEST model to make itmore reliable.•The balance between ...urban development andhabitat quality conservation could be struck in a smart growth scenario.
China has experienced the most serious habitat degradation. Even though increasing attentions have been brought to this issue, we still lack the understanding of the impact of land use change on habitats. This study proposed an integrated framework with cellular automata (CA) scenario simulation and the “Integrated Valuation of Environmental Services and Trade-offs” (InVEST) model to evaluate how different landscape dynamics could exert influences on habitat quality. Unlike other methods, our approach evaluates habitat quality by analyzing land use cover in conjunction with habitat threats. The data needed in the framework is readily available spatial data, the demand is relatively low so that our approach is more useful in the data-scarce situation, and incorporating CA simulation facilitates the predictive scenario analysis. We simulated three alternative future scenarios with different development orientations by CA (fast urban sprawl, smart urban expansion, and ecology conservation scenario), and assessed the habitat quality in each scenario by the InVEST model. Results show that in current (2014) land use scenario, “moderate” grade (habitat quality value: 0.4–0.6) occupies the largest proportion (37.62%), and “poor” grade (0–0.2) area takes up 2.82%, concentrates in urban and peri-urban fringe, which proves the degrading impacts from urbanization. The impact of future land use change varies with different land use scenario: in fast urbanization scenario, the landscape displays complete habitat degradation, while the ecology conservation scenario shows the converse trend. The interesting finding is, the degrading impacts of urbanization could be weakened, or even eliminated by the smart urban growth scenario. It suggests that the trade-off between habitat conservation and urban development could be achieved.
Resveratrol (3,4',5-trihy- droxystilbene), a natural phytoalexin polyphenol, exhibits anti-oxidant, anti-inflammatory, and anti-carcinogenic properties. This phytoalexin is well-absorbed and rapidly ...and extensively metabolized in the body. Inflammation is an adaptive response, which could be triggered by various danger signals, such as invasion by microorganisms or tissue injury. In this review, the anti-inflammatory activity and the mechanism of resveratrol modulates the inflammatory response are examined. Multiple experimental studies that illustrate regulatory mechanisms and the immunomodulatory function of resveratrol both in vivo and in vitro. The data acquired from those studies are discussed.
In order to study pore structure and fractal characteristics of the organic-rich marine shale, fourteen shale samples from Lower Cambrian Qiongzhusi formation in Malong block of eastern Yunnan ...province were investigated by organic geochemical analysis (total organic carbon content analysis and thermal maturity analysis), X-ray diffraction (XRD) analysis, porosity and permeability tests, field emission scanning electron microscopy (FE-SEM), low-pressure nitrogen adsorption and methane adsorption experiments. Fractal dimensions D1 and D2 (at relative pressure of 0–0.5 and 0.5–1, respectively) were obtained from the nitrogen adsorption data using the fractal Frenkel–Halsey–Hill (FHH) method. Not only have the relationships among pore structure parameters of shale, the relationships between TOC content, mineral compositions, pore structure parameters and fractal dimensions been discussed, but also the significance of two fractal dimensions D1 and D2 and the impact of fractal dimensions on adsorption capacity have been investigated. The results showed that fourteen shale samples have TOC content ranging from 1.25% to 7.72%, two fractal dimensions both increase with the increasing TOC content, and gradually come to a standstill—the curves present the shape of “parabola”. The major mineralogical compositions of shales are quartz and clay minerals, the quartz contents are between 25.5% and 42.7%, the clay contents are between 26.6% and 44.2%. Fractal dimension D1 has a negative correlation with quartz contents and a positive correlation with clay minerals contents, but fractal dimension D2 has no apparent relationship with quartz and clay minerals contents. The specific surface area is in the range of 4.98 m2/g–19.66 m2/g, the total pore volume is between 0.00479 cm3/g and 0.01765 cm3/g, and the average pore diameter is between 3.37 nm and 6.02 nm. Two fractal dimensions increase with the increasing surface area and pore volume, and also increase with the decreasing average pore diameter because of the complicated pore surface and structure of small pores. Further investigation indicates that D1 represents fractal characteristics from the irregular pore surface, while D2 represents fractal characteristics related to the complicated pore structure, and shale samples with larger fractal dimensions have higher methane adsorption capacity. Therefore fractal analysis is helpful to have a better understanding of pore structure and adsorption capacity of marine shale.
•Fractal dimensions of 14 marine organic-rich shale core samples were studied.•The relationship between fractal dimensions and TOC content is characterized by a parabolic curve.•Fractal dimensions increase with increasing surface area and total pore volume, and with decreasing average pore diameter.•Shale with greater pore surface fractal dimension and pore structure fractal dimension has higher adsorption capacity.
In this letter, we investigate the distributed autonomous resource selection for LTE vehicle to vehicle (V2V) broadcast. The effectiveness of collision avoidance and location based resource ...allocation enhancements is examined. It is found that collision avoidance with multiple data resources reservation per schedule assignment (SA) is a key to improve broadcast reliability. However, in the existing collision avoidance algorithm reserving multiple resources per SA can lead to many data packet collisions if a SA collision happens. We propose an enhanced collision avoidance to address this issue. The idea is to use selected data packets to disseminate the reservation of data resources and SA resources, which can provide better communication among neighbor vehicles on resource reservation and reduce data collisions. Simulation results show that the proposed collision avoidance enhancement can effectively improve SA and data transmission reliability. The network capacity in terms of supported vehicles under given V2V service requirements is largely increased by 17% at a negligible cost of added overhead.
Analysis of Internet of Things (IoT) sensor data is a key for achieving city smartness. In this paper a multitier fog computing model with large-scale data analytics service is proposed for smart ...cities applications. The multitier fog is consisted of ad-hoc fogs and dedicated fogs with opportunistic and dedicated computing resources, respectively. The proposed new fog computing model with clear functional modules is able to mitigate the potential problems of dedicated computing infrastructure and slow response in cloud computing. We run analytics benchmark experiments over fogs formed by Rapsberry Pi computers with a distributed computing engine to measure computing performance of various analytics tasks, and create easy-to-use workload models. Quality of services (QoS) aware admission control, offloading, and resource allocation schemes are designed to support data analytics services, and maximize analytics service utilities. Availability and cost models of networking and computing resources are taken into account in QoS scheme design. A scalable system level simulator is developed to evaluate the fog-based analytics service and the QoS management schemes. Experiment results demonstrate the efficiency of analytics services over multitier fogs and the effectiveness of the proposed QoS schemes. Fogs can largely improve the performance of smart city analytics services than cloud only model in terms of job blocking probability and service utility.
The aim of this study was to investigate the effect of dietary resveratrol supplementation on innate immunity and inflammatory responses in the spleen of yellow-feather broilers under heat stress. A ...total of 288 yellow-feather broilers of 28-day-old were randomly assigned to 3 treatment groups with 6 replicates. A thermo-neutral group (TN) (24 ± 2°C) received a basal diet and another 2 heat-stressed groups (37 ± 2°C for 8 h/D and 24 ± 2°C for the remaining time) were fed the basal diet (HT) or basal diet with 500 mg/kg resveratrol (HT+Res) for 14 consecutive days. The results showed that heat stress decreased (P < 0.05) the growth index of thymus, spleen, and bursa of Fabricius, reduced (P < 0.05) the levels of complement C3 and C4 in serum. Heat stress also caused activation of inflammatory immune responses evidenced by increased (P < 0.05) the mRNA abundance of HSP (heat shock protein) 70, toll-like receptor (TLR)1, TLR4, TLR5, myeloid differentiation factor-88 (MyD88), nucleotide-binding oligomerization domain 1 (NOD1), Dectin-1, transforming growth factor-β-activated kinase 1 (TAK1), interleukin (IL)-1, IL-4, IL-6, and tumor necrosis factor (TNF)-α, but decreased the mRNA abundance of interferon (IFN)-γ, activated nuclear factor kappa B (NF-κB), mitogen-activated protein kinases (MAPK), and phosphoinositide-3 kinases-protein kinase B (PI3K/AKT) signaling pathways. Dietary supplementation with resveratrol improved (P < 0.05) the growth index of thymus, spleen and bursa Fabricius, and increased (P < 0.05) the serum level of complement C3 under heat stress. In addition, resveratrol reduced (P < 0.05) the mRNA abundance of HSP70, TLR4, TLR5, NOD1, Dectin-1, and TAK1, and inhibited the NF-κB, MAPK and PI3K/AKT signaling pathway via down-regulated the phosphorylation of p65, extracellular signal-regulated kinases 1/2, c-Jun N-terminal protein kinase and AKT, as well as decreased the inflammatory cytokines expression, including IL-1, IL-4, IL-6, and TNF-α in the spleen under heat stress. Collectively, dietary resveratrol could have beneficial effects to regulate innate immunity and inflammatory response, via inhibiting the activation of NF-κB, MAPK, and PI3K/AKT signaling pathways induced by heat stress in the spleen.
Macropore flow not only provides a fast pathway for water and solute transport and increases the risks of water and nutrient loss but also enhances soil aeration and groundwater recharge. However, ...macropore flow characteristics in irrigated oasis soils subject to continuous crop cultivation are poorly understood. This study was to investigate the effect of continuous cultivation on soil properties and macropore flow and to quantify the changes in macropore flow characteristics in an old oasis field (>50 years of cultivation, OOF), young oasis field (20 years, YOF), and adjacent uncultivated sandy area (0 year, USL) in Northwest China. Triplicate soil samples were collected from each site to investigate soil properties. Dye tracer experiments with also three replicates were conducted at each site. The degree of macropore flow (i.e., parameters of macropore flow) was highest at the OOF, intermediate at the YOF, and minimal at the USL. The macropore flow fraction (i.e., fraction of total infiltration flows through macropore flow pathways) at the OOF was 3.4 times greater than at the USL. The heterogeneous infiltration pattern at the OOF was dominated by macropore flow, while funnel flow was predominant at the USL. Long‐term irrigation with silt‐laden river water has increased silt + clay contents of the oasis soils. Irrigation and high‐input crop cultivation also increased organic matter. These changes in soil properties contributed to the interaggregate voids formation. The conversion of native desert soils to irrigated croplands increases the degree of macropore flow, which might enhance groundwater recharge in the desert‐oasis ecotone.
Key Points
Continuous cultivation with river water irrigation enhanced soil properties and the degree of preferential flow
Preferential flow was dominated at old oasis field and young oasis field, while funnel flow was predominant at uncultivated sandy area
Silt and clay content, soil organic carbon, and macroporosity had positive influence on preferential flow occurrence
•Water and energy dynamics over irrigated seed maize agroecosystems were studied.•The seasonal variability of energy flux was quantitatively partitioned.•ET ranged 467–545mm for seed maize with the ...mean daily ET 2.84–3.35mmday−1.•Daily ET was mainly controlled by net radiation, LAI, canopy conductance, and irrigation.
Investigating the dynamics of energy and water vapor exchange in oasis agroecosystems is important to improve scientific understanding of land surface processes in desert-oasis regions. In this study, water vapor and energy fluxes were obtained by using an eddy covariance technique for two similar irrigated seed maize fields at Yingke and Pingchuan, in northwest China. Seasonal variabilities of evapotranspiration (ET) and relevant environmental and biophysical factors were explored. Results showed that the energy balance closures were reasonable, with energy balance ratio of 0.99 and 0.79 for a half-hourly time scale at Yingke and Pingchuan, respectively. The seasonal changes in net radiation (Rn), latent heat flux (LE), and sensible heat flux (H) of Yingke and Pingchuan were similar. Net radiation was 11.27MJm−1day−1 during the growing season. Latent heat flux accounted for 67.5% of net radiation, sensible heat flux was 25.0%, and soil heat flux was 7.5%. A reverse seasonal change was found in partitioning energy flux into LE and H. The seasonal variation in energy flux partitioning was significantly related to the phenology of maize. During the growing season, ET was 467 and 545mm, and mean daily ET 2.84 and 3.35mmday−1 at Pingchuan and Yingke, respectively. “Non-growing” season ET was 15% of the annual ET in the bare field (during October–March) and 85% of the annual ET for maize (during April–September). Daily ET was mainly controlled by net radiation and air temperature, and was significantly affected by leaf area index (<3.0m2m−2) and canopy conductance (<10mms−1). Furthermore, irrigation promoted daily ET greatly during the growing season. Accurate estimation of seed maize ET and determination the controlling factors helps to develop exact irrigation scheduling and improve water resource use in desert-oasis agroecosystems.
PDF
