1,672 research outputs found
VARIABILITY OF NO AND NO2 ABOVE THE SNOWPACK AT SUMMIT, GREENLAND
Nitric oxide (NO) and nitrogen dioxide (NO2) were measured at levels of approximately 7.5 m, 3 m, and 0.5 m above the surface snowpack at Summit, Greenland from July 2008 to July 2010, respectively, with two sets of instrument systems. Instrument I measured NO and NO2 at levels of 3 m and 0.5 m with two inlets, and instrument II measured NO and NO2 at a level of 7.5 m plus total reactive nitrogen oxides (NOy) at the same level with one inlet. Compared to previous measurements, the data provided the first year-round simultaneous record of NO and NO2 at different levels above the snowpack at a high latitude Arctic site.
Apparent seasonal and diurnal cycles were observed for both NO and NO2 at different levels. NO reached high levels when solar radiation was high from late spring to summer in a seasonal scale and at around noon in a diurnal scale, while NO2 reached high levels from early spring to early fall in a seasonal scale and from afternoon to night in a diurnal scale. The vertical gradients of NO and NO2 between 3 m and 0.5 m above the snowpack suggested the emission of NO from the surface snowpack. An improved mechanism for snowpack photochemistry at Summit is proposed to explain the seasonal variability of NO and NO2. Furthermore, a pollution event study showed that FLEXPART retroplume simulations were in agreement with the measurements. During polar night season, NO2 exactly followed FLEXPART simulation. Nitrate accumulation through snowpack deposition was proposed to attribute NO2 increase in early spring. In sunlight season, nitrate deposition was proposed to occur during the pollution events and was re-emitted from the snowpack via photolysis after the event, resulting in subsequent NO2 increase
RESIDENTIAL ENERGY DEMAND AND ENERGY EFFICIENCY
The first essay investigates the relatively higher energy efficiency (EE) investment rates in housing units of homeowners versus those of renters. In the empirical analysis, discrete choice models are employed to explore households\u27 EE investment behavior. After testing three groups of implications derived from the initial analysis, the paper suggests that due to the existence of contracting costs, landlords/renters make efficient decisions to invest less in EE than homeowners due to renters\u27 increased mobility and the characteristics of typical EE investments. The second essay analyzes households\u27 choices of energy efficient dishwashers and the potential influence from those choices on dish washing behavior. An ordered Probit model is developed to investigate households\u27 demand for dish washing services. Two-stage residual inclusion (2SRI) is used to deal with the endogeneity problem, caused by households choosing energy efficient dishwashers because of higher expected usage frequency. Households using energy efficient dish washers compared with households using standing dishwashers display approximately 7.7% more frequent usage behavior. The final essay examines U.S. residential consumption of four main fuels. Double-log demand models are applied and two-stage residual inclusion is used to address price endogeneity. Besides various elasticity estimates, the paper further explores causes of the rising per capital electricity consumption over time despite the efficiency progress. Historical survey data reveal that households increase electricity consumption by increasing the quantity of electronics and/or purchasing electronics with extra energy-consuming attributes
Distributed sampled-data control of nonholonomic multi-robot systems with proximity networks
This paper considers the distributed sampled-data control problem of a group
of mobile robots connected via distance-induced proximity networks. A dwell
time is assumed in order to avoid chattering in the neighbor relations that may
be caused by abrupt changes of positions when updating information from
neighbors. Distributed sampled-data control laws are designed based on nearest
neighbour rules, which in conjunction with continuous-time dynamics results in
hybrid closed-loop systems. For uniformly and independently initial states, a
sufficient condition is provided to guarantee synchronization for the system
without leaders. In order to steer all robots to move with the desired
orientation and speed, we then introduce a number of leaders into the system,
and quantitatively establish the proportion of leaders needed to track either
constant or time-varying signals. All these conditions depend only on the
neighborhood radius, the maximum initial moving speed and the dwell time,
without assuming a prior properties of the neighbor graphs as are used in most
of the existing literature.Comment: 15 pages, 3 figure
The Use of Stance Markers in Chinese and International Journal Abstracts in Aerospace
Stance in academic discourse refers to the writer-oriented approach to interact with readers by commenting on the credibility of propositions, expressing their own attitudes or mentioning themselves. This study compares and analyzes the overall distribution and differences of the use of stance markers in Chinese and international journal abstracts. The corpus includes 200 journal abstracts from the both top 10 Chinese and international academic journals of aerospace discipline from 2018 to 2022. The results show that Chinese and international journal abstracts frequently use stance markers to express author’s attitudes and the following pattern appears in both journals according to the frequency of use, that is, epistemic stance markers> attitude markers > self-mention. Meanwhile, Chinese and international journals differ significantly in the use of approximators, shields, affect markers, first person self-mention and third person self-mention. International journals also seem to adopt more hedges than boosters, while Chinese journals adopt more boosters than hedges. A comparative analysis of stance markers could provide some reference for Chinese authors in writing academic abstracts
Variational Quantum Singular Value Decomposition
Singular value decomposition is central to many problems in engineering and
scientific fields. Several quantum algorithms have been proposed to determine
the singular values and their associated singular vectors of a given matrix.
Although these algorithms are promising, the required quantum subroutines and
resources are too costly on near-term quantum devices. In this work, we propose
a variational quantum algorithm for singular value decomposition (VQSVD). By
exploiting the variational principles for singular values and the Ky Fan
Theorem, we design a novel loss function such that two quantum neural networks
(or parameterized quantum circuits) could be trained to learn the singular
vectors and output the corresponding singular values. Furthermore, we conduct
numerical simulations of VQSVD for random matrices as well as its applications
in image compression of handwritten digits. Finally, we discuss the
applications of our algorithm in recommendation systems and polar
decomposition. Our work explores new avenues for quantum information processing
beyond the conventional protocols that only works for Hermitian data, and
reveals the capability of matrix decomposition on near-term quantum devices.Comment: 23 pages, v3 accepted by Quantu
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