55,483 research outputs found
The Neutrophil/Lymphocyte Ratio Could Predict Noninvasive Mechanical Ventilation Failure in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Retrospective Observational Study [Corrigendum]
No full textSun W, Luo Z, Jin J, Cao Z, Ma Y. Int J Chron Obstruct Pulmon Dis. 2021;16:2267–2277.
The authors have advised the author list on page 2267 is incorrect. The text “Yingmin Ma2” should read “Yingmin Ma1,2”.
The authors apologize for this error
In situ construction of CoSe 2 @vertical-oriented graphene arrays as self-supporting electrodes for sodium-ion capacitors and electrocatalytic oxygen evolution
No full textTransitional metal dichacogenides (TMDs) have stimulated an increasing research and technological attention due to their unique properties, holding great promise for emerging energy storage and conversion applications. However, tailorable and efficient synthesis of TMDs to garner the electrochemical and electrocatalytic performance of thus-derived electrodes has by far remained challenging. Herein we demonstrate a versatile synthetic strategy to in situ grow CoSe 2 @vertically-oriented graphene (VG) hierarchical architecture on carbon fiber cloth (CC) via combined steps of plasma-enhanced chemical vapor deposition and wet chemistry. Such self-supporting and flexible CoSe 2 @VG/CC arrays possess significant implications for pseudocapacitive Na storage and electrocatalytic O 2 evolution (OER). When evaluated as an anode material for sodium-ion hybrid capacitors, full cells comprising a CoSe 2 @VG/CC anode and AC cathode enable a favorable cyclic stability at 0.5 A g −1 for 1800 cycles in the potential range of 0.5–3.3 V, harvesting a high energy and power density of 116 Wh kg −1 and 7298 W kg −1 . In addition, CoSe 2 @VG/CC array also exhibits an excellent OER performance with a low overpotential of 418 mV and Tafel slope of 82 mV dec −1 on a basis of experimental exploration and theoretical simulation
Relative Orbit-Attitude Tracking for Spacecraft Using Adaptive Fast Terminal Sliding Mode Control
No full text-analogues of two supercongruences of Z.-W. Sun
No full textsummary:We give several different -analogues of the following two congruences of \hbox {Z.-W. Sun}: where is an odd prime, is a positive integer, and is the Jacobi symbol. The proofs of them require the use of some curious -series identities, two of which are related to Franklin's involution on partitions into distinct parts. We also confirm a conjecture of the latter author and Zeng in 2012
Designing 3D Biomorphic Nitrogen-Doped MoSe2/Graphene Composites toward High-Performance Potassium-Ion Capacitors
No full textPotassium-ion hybrid capacitors (KICs) reconciling the advantages of batteries and supercapacitors have stimulated growing attention for practical energy storage because of the high abundance and low cost of potassium sources. Nevertheless, daunting challenge remains for developing high-performance potassium accommodation materials due to the large radius of potassium ions. Molybdenum diselenide (MoSe2) has recently been recognized as a promising anode material for potassium-ion batteries, achieving high capacity and favorable cycling stability. However, KICs based on MoSe2 are scarcely demonstrated by far. Herein, a diatomite-templated synthetic strategy is devised to fabricate nitrogen-doped MoSe2/graphene (N-MoSe2/G) composites with favorable pseudocapacitive potassium storage targeting a superior anode material for KICs. Benefiting from the unique biomorphic structure, high electron/K-ion conductivity, enriched active sites, and the conspicuous pseudocapacitive effect of N-MoSe2/G, thus-derived KIC full-cell manifests high energy/power densities (maximum 119 Wh kg−1/7212 W kg−1), outperforming those of recently reported KIC counterparts. Furthermore, the potassium storage mechanism of N-MoSe2/G composite is systematically explored with the aid of first-principles calculations in combination of in situ X-ray diffraction and ex situ Raman spectroscopy/transmission electron microscopy/X-ray photoelectron spectroscopy
Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks
No full textFacial image synthesis has been extensively studied, for a long time, in both computer graphics and computer vision. Particularly, the synthesis of face images with varying ages, expressions and poses has received an increasing attention owing to several real-world applications. In this paper, facial age and expression synthesis are addressed. While previous and current research papers on facial age synthesis mostly adopt an age span of 10 years, this paper investigates face aging with a shorter time span. For expression synthesis, given a neutral face, we work on synthesizing faces with varying expression intensities (e.g., from zero to high). Note that both human ages and expression intensities are inherently ordinal. To fully exploit this ordinal nature, we devise ordinal ranking generative adversarial networks (ranking GAN). For each face, a one-hot label is assigned to define its age range/expression intensity. By exploiting the relative order information among age ranges/expression intensities, a binary ranking vector is further computed for each face. In ranking GAN, one-hot labels are used as the condition of the generator for synthesizing faces with target age groups/expression intensities. Moreover, we add a sequence of cost-sensitive ordinal rankers on top of several multi-scale discriminators, with the aim of minimizing age/intensity rank estimation loss when optimizing both the generator and discriminators. In order to evaluate the proposed ranking GAN, extensive experiments are carried out on several public face databases. As demonstrated by the experimental testing, this ranking scheme performs well even when the amount of available labeled training data is limited. The reported experimental results well demonstrate the effectiveness of ranking GAN on synthesizing face aging sequences and faces with varying expression intensities
Facial Age Synthesis with Label Distribution-Guided Generative Adversarial Network
No full textThe existing research work on facial age synthesis has been mostly focused on long-term aging (e.g., over an age span of 10 years or more). In this paper, we employ generative adversarial networks (GANs) as a tool to investigate age synthesis over different age spans. Compared with long-term aging, short-term age synthesis suffers from the reduced amount of available training data, which can severely hinder the model training. We conduct a series of experiments to validate this. To facilitate short-term age synthesis, we further propose label distribution-guided generative adversarial network (ldGAN), where each sample is associated with an age label distribution (ALD) rather than a single age group. Accordingly, each sample can contribute not only to the learning of its own age group but also to neighbouring groups' learning. This is useful when addressing short-term aging to cope with the reduced amount of training data. In addition, unlike one-hot encoding which treats age groups as independent from one another, ldGAN can well capture the correlation among different age groups, so that smooth aging sequences can be achieved. The ALD model is integrated into GAN with a two-step process. Firstly, instead of the traditional one-hot encoding, ALD is applied as the condition of the generator. Secondly, we add a sequence of label distribution learners on top of several multi-scale discriminators, with the aim of minimizing the label distribution learning loss when optimizing both the generator and discriminators. Both qualitative and quantitative evaluations are conducted to assess ldGAN's ability in dealing with two core issues of face aging, i.e., aging effect generation and identity preservation. The obtained experimental results demonstrate the effectiveness of ldGAN in both learning short-term aging patterns and coping with the lack of training data
Review of the book How Fascism Works, by J. Stanley
No full textDr. Devin Z. Shaw (Douglas College) reviews the book How fascism works, by J. Stanley (2020).Final article published
A set based probabilistic approach to threshold design for optimal fault detection
No full textTraditional deterministic robust fault detection threshold designs, such as the norm-based or limit-checking method, are plagued by high conservativeness, which leads to poor fault detection performance. On one side they are ill-suited at tightly bounding the healthy residuals of uncertain nonlinear systems, as such residuals can take values in arbitrarily shaped, possibly non-convex regions. On the other hand, they must be robust even to worst-case, rare values of the modeling and measurement uncertainties. In order to maximize performance of detection, we propose two innovative ideas. First, we introduce threshold sets, parametrized in a way to bound arbitrarily well the residuals produced in healthy condition by an observer-based residual generator. Secondly, we formulate a chance-constrained cascade optimization problem to determine such a set, leading to optimal detection performance of a given class of faults, while guaranteeing robustness in a probabilistic sense. We then provide a computationally tractable framework by using randomization techniques, and a simulation analysis where a well-known three-tank benchmark system is considered.Accepted Author ManuscriptTeam Tamas KeviczkyTeam Jan-Willem van Wingerde
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