30,765 research outputs found
q-Differential equations for q-classical polynomials and q-Jacobi-Stirling numbers
No full textWe introduce, characterise and provide a combinatorial interpretation for the so-called q-Jacobi–Stirling numbers.
This study is motivated by their key role in the (reciprocal) expansion of any power of a second order
q-differential operator having the q-classical polynomials as eigenfunctions in terms of other even order operators,
which we explicitly construct in this work. The results here obtained can be viewed as the q-version of
those given by Everitt et al. and by the first author, whilst the combinatorics of this new set of numbers is a
q-version of the Jacobi–Stirling numbers given by Gelineau and the second author
Cissampelos keniensis Y. D. Zhou & Q. F. Wang
No full textE Cissampelos keniensis Y.D.Zhou & Q.F.Wang — Habit: Liana. Habitat: LMWF; 2 000–2 300 m. Distribution: IIIc. Voucher: Kaburia Track, Alt. 2 241 m, 29 Jun. 2016, Zhou & Mbuni 16/14 (HIB, EA, PE). Reference: Zhou et al. (2017b).Published as part of Zhou, Ya-Dong, Mwachala, Geoffrey, Hu, Guang-Wan & Wang, Qing-Feng, 2022, Annotated checklist of the vascular plants of Mount Kenya, East Africa, pp. 1-108 in Phytotaxa 546 (1) on page 41, DOI: 10.11646/phytotaxa.546.1.1, http://zenodo.org/record/655046
Zehneria subcoriacea Y. D. Zhou & Q. F. Wang
No full textZehneria subcoriacea Y.D.Zhou & Q.F.Wang — Habit: Climber. Habitat: LMWF, BZ, UMF; 2 000–3 200 m. Distribution: IIIa. Voucher: Naro Moru Track, near Met. Station, Alt. 3065 m, 27 Jun. 2016, Zhou & Mbuni 16/3 (HIB, EA, PE). Reference: Zhou et al. (2016b).Published as part of Zhou, Ya-Dong, Mwachala, Geoffrey, Hu, Guang-Wan & Wang, Qing-Feng, 2022, Annotated checklist of the vascular plants of Mount Kenya, East Africa, pp. 1-108 in Phytotaxa 546 (1) on page 52, DOI: 10.11646/phytotaxa.546.1.1, http://zenodo.org/record/655046
Association between Wind Environment and Spatial Characteristics of High-Rise Residential Buildings in Cold Regions through Field Measurements in Xi’an
No full textResearch on the correlation between wind and block spatial form focuses mainly on hot and humid cities. However, cold regions are also experiencing high summer temperatures due to global climate change. Enhancing wind speed in blocks through urban spatial control improves comfort. Existing research cannot be directly applied to cold regions due to natural differences. Using Xi’an as an example, this study explores the impact of high-rise residential block spatial form on internal and external wind environments through field measurements and simulations. Optimal strategies for block planning and architectural design are identified to improve the wind environment. Results show that blocks with high buildings on the south and north sides and low buildings in the middle achieve a more comfortable internal wind environment. Gradually increasing building height from south to north has minimal impact on downwind blocks. Reducing the angle between the main facade and dominant wind direction enhances the residential area’s wind environment. Specific spatial planning and design strategies are summarized for early-stage decision-making
d-q axis current waveform when the motor starts.
No full textd-q axis current waveform when the motor starts.</p
d-q axis current waveform when the given speed changes.
No full textd-q axis current waveform when the given speed changes.</p
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Gradient Feature-Oriented 3-D Domain Adaptation for Hyperspectral Image Classification
No full textDomain adaptation, which cleverly applies the classifier learned from the source domain with sufficient labeled samples to the target domain with limited labeled samples, provides a feasible alternative to handle the small training sample problem of hyperspectral image (HSI) classification and has attracted much attention in the research field recently. Apparently, feature discriminative ability is vital for domain adaptation, which plays a crucial role during the migration process of transfer learning. In this article, a gradient feature-oriented 3-D domain adaptation (GF-3DDA) approach is proposed for HSI classification. First, 3-D Gabor is employed to remove noise from the original data, and two 2-D gradient-based features, 2-D Sobel gradient (SG) and 2-D derivative-of-Gaussian (DtG), are extended to the 3-D domain to coincide with the integrated spatial-spectral organization of HSI. Thus, the 3-D Sobel-Gabor gradient (3DSGG) and 3-D derivative-of-Gaussian-Gabor (3DDGG) features are achieved. Second, a 3-D domain adaptation method is implemented to jointly exploit the second- and fourth-order statistical descriptors in the spatial-spectral dimensions, which could effectively reduce domain shifts and thus achieve improved domain adaptation. Third, all the extracted domain-adapted feature modules are collaboratively classified by extreme learning machine (ELM), and the probability-like outputs of every ELM classifier are combined together to accomplish the classification task. Four hyperspectral data sets that each contains two scenes, i.e., Pavia, Shanghai-Hangzhou, Indiana, and Houston, are tested in the experiments. When only ten labeled samples per class are used in the target domain, the classification accuracies on four hyperspectral data sets achieved by our GF-3DDA approach are 93.31%, 84.35%, 69.32%, and 80.06%, respectively.No Full Tex
Modeling Fuel-Air Mixing, Combustion and Soot Formation with Ducted Fuel Injection Using Tabulated Kinetics
No full textDucted Fuel Injection (DFI) has the potential to reduce soot emissions in Diesel engines thanks to the enhanced mixing rate resulting from the liquid fuel flow through a small cylindrical pipe located at a certain distance from the nozzle injector hole. A consolidated set of experiments in constant-volume vessel and engine allowed to understand the effects of ambient conditions, duct geometry and shape on fuel-air mixing, combustion and soot formation. However, implementation of this promising technology in compression-ignition engines requires predictive numerical models that can properly support the design of combustion systems in a wide range of operating conditions. This work presents a computational methodology to predict fuel-air mixing and combustion with ducted fuel injection. Attention is mainly focused on turbulence and combustion modelling. The first is mainly responsible for the mixture formation process in presence of large velocity gradients and flow recirculations, while the second must include detailed kinetics and turbulence chemistry-interaction to correctly predict ignition delay and flame structure. Literature experimental data were used for model assessment and validation under different ambient conditions considering both free-spray and ducted fuel injection configurations. Two different RANS turbulence models were tested (k - ? and k- ? -SST) to evaluate how they describe the flow in the duct region and the air/fuel mixing occurring downstream. Afterwards, combustion simulations were carried out using a tabulated flamelet progress variable model based on auto-ignition calculations of diffusion flames using detailed kinetics. Experimental data of ignition delay, flame lift-off and soot mass evolution were used to validate the proposed approach
Sedum keniense Y. D. Zhou, G. W. Hu & Q. F. Wang
No full textE Sedum keniense Y.D.Zhou, G.W.Hu & Q.F.Wang — Habit: Herb. Habitat: HZ; 3 000–3 200 m. Distribution: IIIc. Voucher: Chogoria Waterfall, Alt. 3 184 m, 25 Jan. 2015, SAJIT 002822 (HIB, PE, EA). Reference: Zhou et al. (2016a).Published as part of Zhou, Ya-Dong, Mwachala, Geoffrey, Hu, Guang-Wan & Wang, Qing-Feng, 2022, Annotated checklist of the vascular plants of Mount Kenya, East Africa, pp. 1-108 in Phytotaxa 546 (1) on page 43, DOI: 10.11646/phytotaxa.546.1.1, http://zenodo.org/record/655046
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