A novel PWM modulation and hybrid control scheme for grid-connected unipolar inverters

The purpose of this paper is to provide low cost, high power quality and high efficiency solutions for grid-connected inverters. Compared with bipolar switched inverters, unipolar switched inverters have the advantages of higher efficiency due to reduced switching frequency and low iron losses of inductor in output filter. However, unipolar inverters produce large harmonic distortion due to the dead-time effects. To address this issue and achieve higher efficiency, a new PWM modulation and a hybrid current control scheme is proposed. Firstly, according to the polarity of current reference, in each leg, the gate drive signal of positive or negative switch is removed, and the dead-time insertion is eliminated. With this modulation method, the inverter circuit operations are divided into six operation modes, and their mathematical models are derived. According to this mathematical model, a hybrid control scheme is proposed that consists of a PI controller and an open-loop controller. The PI controller operates in the linear areas, and the open-loop controller operates in the nonlinear areas. Several control rules are designed to realize smooth transition between different control modes. With this control scheme, firstly, the influence of dead-time can be eliminated, and the harmonic distortion can be greatly reduced. Without the influence of switching dead-time, the dc-link voltage can be minimized that will contribute to reduced switching losses and smaller ripple current. The proposed control scheme is verified with simulation and experimental results. The experimental test is implemented in a 10 kW single-phase grid-connected inverter that uses a DSP controller TMS320F2808. The reductions of conversion losses, low harmonic distortion and low ripple current are all confirmed in the experimental system. The comparisons between the conventional control scheme and the proposed scheme are presented in this paper.2011 IEEE Applied Power Electronics Conference and Exposition - APEC 2011 : Fort Worth, TX, USA, 2011.03.6-2011.03.1

Increased Dependence of Humans on Ecosystem Services and Biodiversity

Humans have altered ecosystems more rapidly and extensively than ever, largely to meet rapidly growing demands for resources along with economic development. These demands have been considered important drivers of ecosystem degradation and biodiversity loss. Are humans becoming less dependent on ecosystem services and biodiversity following economic development? Here, we used roundwood production, hydroelectricity generation and tourism investment in 92 biodiversity hotspot and 60 non-hotspot countries as cases to seek the answer. In 1980–2005, annual growth rates of roundwood production, hydroelectricity generation and tourism investment were higher in hotspot countries (5.2, 9.1 and 7.5%) than in non-hotspot countries (3.4, 5.9 and 5.6%), when GDP grew more rapidly in hotspot countries than non-hotspot countries. Annual growth rates of per capita hydropower and per capita tourism investment were higher in hotspot countries (5.3% and 6.1%) than in non-hotspot countries (3.5% and 4.3%); however, the annual growth rate of per capita roundwood production in hotspot countries (1%) was lower than in non-hotspot countries (1.4%). The dependence of humans on cultural services has increased more rapidly than on regulating services, while the dependence on provisioning services has reduced. This pattern is projected to continue during 2005–2020. Our preliminary results show that economic growth has actually made humans more dependent upon ecosystem services and biodiversity. As a consequence, the policies and implementations of both economic development and ecosystems/biodiversity conservation should be formulated and carried out in the context of the increased dependence of humans on ecosystem services along with economic development

Anharmonic phonon-phonon scattering at interface by non-equilibrium Green's function formalism

The understanding and modeling of inelastic scattering of thermal phonons at a solid/solid interface remain an open question. We present a fully quantum theoretical scheme to quantify the effect of anharmonic phonon-phonon scattering at an interface via non-equilibrium Green's function (NEGF) formalism. Based on the real-space scattering rate matrix, a decomposition of the interfacial spectral energy exchange is made into contributions from local and non-local anharmonic interactions, of which the former is shown to be predominant for high-frequency phonons whereas both are important for low-frequency phonons. The anharmonic decay of interfacial phonon modes is revealed to play a crucial role in bridging the bulk modes across the interface. The overall quantitative contribution of anharmonicity to thermal boundary conductance is found to be moderate. The present work promotes a deeper understanding of heat transport at the interface and an intuitive interpretation of anharmonic phonon NEGF formalism

Assessing Phonon Coherence Using Spectroscopy

As a fundamental physical quantity of thermal phonons, temporal coherence participates in a broad range of thermal and phononic processes, while a clear methodology for the measurement of phonon coherence is still lacking. In this Lettter, we derive a theoretical model for the experimental exploration of phonon coherence based on spectroscopy, which is then validated by comparison with Brillouin light scattering data and direct molecular dynamic simulations of confined modes in nanostructures. The proposed model highlights that confined modes exhibit a pronounced wavelike behavior characterized by a higher ratio of coherence time to lifetime. The dependence of phonon coherence on system size is also demonstrated from spectroscopy data. The proposed theory allows for reassessing data of conventional spectroscopy to yield coherence times, which are essential for the understanding and the estimation of phonon characteristics and heat transport in solids in general.Comment: 4 pages, 3 figure

Congener diversity, topographic heterogeneity and human‐assisted dispersal predict spread rates of alien herpetofauna at a global scale

Understanding the factors that determine rates of range expansion is not only crucial for developing risk assessment schemes and management strategies for invasive species, but also provides important insight into the ability of species to disperse in response to climate change. However, there is little knowledge on why some invasions spread faster than others at large spatiotemporal scales. Here, we examine the effects of human activities, species traits and characteristics of the invaded range on spread rates using a global sample of alien reptile and amphibian introductions. We show that spread rates vary remarkably among invaded locations within a species, and differ across biogeographical realms. Spread rates are positively related to the richness of native congeneric species and human‐assisted dispersal in the invaded range but are negatively correlated with topographic heterogeneity. Our findings highlight the importance of environmental characteristics and human‐assisted dispersal in developing robust frameworks for predicting species' range shifts.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107378/1/ele12286.pd

Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation

Session-based recommendation (SBR) systems aim to utilize the user's short-term behavior sequence to predict the next item without the detailed user profile. Most recent works try to model the user preference by treating the sessions as between-item transition graphs and utilize various graph neural networks (GNNs) to encode the representations of pair-wise relations among items and their neighbors. Some of the existing GNN-based models mainly focus on aggregating information from the view of spatial graph structure, which ignores the temporal relations within neighbors of an item during message passing and the information loss results in a sub-optimal problem. Other works embrace this challenge by incorporating additional temporal information but lack sufficient interaction between the spatial and temporal patterns. To address this issue, inspired by the uniformity and alignment properties of contrastive learning techniques, we propose a novel framework called Session-based Recommendation with Spatio-Temporal Contrastive Learning Enhanced GNNs (RESTC). The idea is to supplement the GNN-based main supervised recommendation task with the temporal representation via an auxiliary cross-view contrastive learning mechanism. Furthermore, a novel global collaborative filtering graph (CFG) embedding is leveraged to enhance the spatial view in the main task. Extensive experiments demonstrate the significant performance of RESTC compared with the state-of-the-art baselines e.g., with an improvement as much as 27.08% gain on HR@20 and 20.10% gain on [email protected]: Under reviewing draft of ACM TOI