Technological progress plays a key role in promoting energy efficiency. In order to find the suitable path of technological progress to improve energy efficiency, this study adopts the ...growth-accounting method to investigate the effects of two types of technological progress, namely, the Hicks-neutral and the capital-embodied technological progress on the changes in energy productivity. Furthermore, dynamic panel data models are applied to investigate the various effects of these two types of technological progress on energy productivities 30 Chinese provinces from 1997 to 2012. The main results are: (1) the Hicks-neutral technological progress directly contributes to energy productivity improvement, and its indirect contribution comes from the optimization of manufacturing structure induced by technological catch-up; (2) the capital-embodied technological progress has a direct contribution to energy productivity improvement, while the indirect contribution is seen through its interaction with the upgrading of the manufacturing structure; (3) the energy-saving performance from the capital-embodied technological progress is poor because of energy rebound effect. These findings suggest that the capital-embodied technological progress is effective for energy-saving in China; which can be made possible only by implementing energy price reforms.
•We improved the Malmquist productivity index.•Two types of technological progress have different effects on energy productivity.•Capital-embodied technical progress is the main contributor of energy-saving.•Energy prices reform is an essential supporting measure.
Compressed air energy storage (CAES) can mitigate fluctuations of renewable-energy output due to its large-scale storage capacities, high ramp rate, and quick start-up time. It has become a novel ...choice for energy storage in microgrids. An islanded microgrid, which consists of wind turbines (WTs), photovoltaic (PV) array, diesel generators, and CAES, is investigated in this paper. The constant-pressure CAES is modeled in terms of its power capacity and energy capacity. A bi-level program (BLP) is proposed for the microgrid planning problem. It considers optimization of operation at the design stage of microgrids. The sizing problem is formulated on the upper level (UL), while the unit commitment (UC) problem with spinning-reserve requirement for the microgrid is described on the lower level (LL). The effectiveness of the approach is validated by case studies where the proposed methodology is compared to other similar ones.
This paper aims to explore the effects of earthquakes on the properties of medium-height reinforced concrete houses in China. The results demonstrated a significant decrease in ultrasonic resonance ...frequency, indicating structural damage, with reductions of 26.5 %, 30.2 %, and 37 % observed for earthquakes of magnitudes 5.0, 5.3, and 5.7, respectively. Similarly, the dynamic modulus of elasticity exhibited a reduction of over 50 %. Measurements of carbonation depth revealed values of 34.65 mm, 38.97 mm, and 46.12 mm for earthquakes of magnitudes 5.0, 5.3, and 5.7, respectively. Accordingly, the percentage of mass loss amounted to 22.17 %, 36.87 %, and 49.78 %. Furthermore, experiments identified the least favourable outcomes during maximum seismic activity, with a recorded peak stress of 447.3 MPa at a deformation of 0.63 mm. These findings contribute to a better understanding of the impact of seismic events on reinforced concrete structures and the associated corrosion mechanisms.
Immune system evasion, distance tumor metastases, and increased cell proliferation are the main reasons for the progression of non-small cell lung cancer (NSCLC) and the death of NSCLC patients. ...Dysregulation of circular RNAs plays a critical role in the progression of NSCLC; therefore, further understanding the biological mechanisms of abnormally expressed circRNAs is critical to discovering novel, promising therapeutic targets for NSCLC treatment.
The expression of circular RNA fibroblast growth factor receptor 1 (circFGFR1) in NSCLC tissues, paired nontumor tissues, and cell lines was detected by RT-qPCR. The role of circFGFR1 in NSCLC progression was assessed both in vitro by CCK-8, clonal formation, wound healing, and Matrigel Transwell assays and in vivo by a subcutaneous tumor mouse assay. In vivo circRNA precipitation, RNA immunoprecipitation, and luciferase reporter assays were performed to explore the interaction between circFGFR1 and miR-381-3p.
Here, we report that circFGFR1 is upregulated in NSCLC tissues, and circFGFR1 expression is associated with deleterious clinicopathological characteristics and poor prognoses for NSCLC patients. Forced circFGFR1 expression promoted the migration, invasion, proliferation, and immune evasion of NSCLC cells. Mechanistically, circFGFR1 could directly interact with miR-381-3p and subsequently act as a miRNA sponge to upregulate the expression of the miR-381-3p target gene C-X-C motif chemokine receptor 4 (CXCR4), which promoted NSCLC progression and resistance to anti-programmed cell death 1 (PD-1)- based therapy.
Taken together, our results suggest the critical role of circFGFR1 in the proliferation, migration, invasion, and immune evasion abilities of NSCLC cells and provide a new perspective on circRNAs during NSCLC progression.
In this paper, a novel rational function approximation method, namely, model-based vector fitting (MVF), is proposed for accurate extraction of the characteristic functions of a coupled-resonator ...diplexer with a resonant type of junction from noise-contaminated measurement data. MVF inherits all the merits of the vector-fitting (VF) method and can also stipulate the order of the numerator of the model. Thus, MVF is suitable for the high-order diplexer system identification problem against measurement noise. With the extracted characteristic functions, a three-port transversal coupling matrix of a diplexer can be synthesized. A matrix orthogonal transformation strategy is also proposed to transform the obtained transversal matrix to a target coupling matrix configuration, whose entries have one-to-one relationship with the physical tuning elements. The whole model extraction procedure is analytical and robust, and can be used in a computer-aided tuning (CAT) program for coupled-resonator diplexers. A practical tuning example of a diplexer with a common resonator is given in detail to demonstrate the effectiveness and the practical value of the proposed method.
Double perovskites (DPs) are one of the most promising candidates for developing white light‐emitting diodes (WLEDs) owing to their intrinsic broadband emission from self‐trapped excitons (STEs). ...Translation of three‐dimensional (3D) DPs to one‐dimensional (1D) analogues, which could break the octahedral tolerance factor limit, is so far remaining unexplored. Herein, by employing a fluorinated organic cation, we report a series of highly luminescent 1D DP‐inspired materials, (DFPD)2MIInBr6 (DFPD=4,4‐difluoropiperidinium, MI=K+ and Rb+). Highly efficient warm‐white photoluminescence quantum yield of 92 % is achieved by doping 0.3 % Sb3+ in (DFPD)2KInBr6. Furthermore, single‐component warm‐WLEDs fabricated with (DFPD)2KInBr6:Sb yield a luminance of 300 cd/m2, which is one of the best‐performing lead‐free metal‐halides WLEDs reported so far. Our study expands the scope of In‐based metal‐halides from 3D to 1D, which exhibit superior optical performances and broad application prospects.
We report on a new class of 1D double perovskite‐inspired materials (DFPD)2MIInBr6 (DFPD=4,4‐difluoropiperidinium, MI=K+ and Rb+), which exhibit an intrinsic warm‐white light emission. Further enhancement is achieved by 0.3 % Sb3+ doping, which boosts PLQY to ≈92 %. Warm white light‐emitting diodes based on single component (DFPD)2KInBr6:Sb are fabricated.
When solving constrained multiobjective optimization problems, an important issue is how to balance convergence, diversity, and feasibility simultaneously. To address this issue, this paper proposes ...a parameter-free constraint handling technique, a two-archive evolutionary algorithm, for constrained multiobjective optimization. It maintains two collaborative archives simultaneously: one, denoted as the convergence-oriented archive (CA), is the driving force to push the population toward the Pareto front; the other one, denoted as the diversity-oriented archive (DA), mainly tends to maintain the population diversity. In particular, to complement the behavior of the CA and provide as much diversified information as possible, the DA aims at exploring areas under-exploited by the CA including the infeasible regions. To leverage the complementary effects of both archives, we develop a restricted mating selection mechanism that adaptively chooses appropriate mating parents from them according to their evolution status. Comprehensive experiments on a series of benchmark problems and a real-world case study fully demonstrate the competitiveness of our proposed algorithm, in comparison to five state-of-the-art constrained evolutionary multiobjective optimizers.
This paper presents an LC low-pass π network to decouple a pair of coupled antennas working at low frequencies. Comparing with existing decoupling techniques, the proposed decoupling network provides ...a wideband but compact decoupling solution. Moreover, a generalized one-fit-all scheme is justified to implement the decoupling network with an antenna independent core network. By adjusting a few external components, the same core network can be applied to a collection of antenna pairs with different coupling levels and antenna form factors. Four design examples are given to demonstrate the unique features of the proposed network for low-frequency applications. In all cases, the decoupling network significantly improves the isolation between two antennas over a wide frequency band while the intrinsic matching bandwidth of the antennas is maintained.
Achieving balance between convergence and diversity is a key issue in evolutionary multiobjective optimization. Most existing methodologies, which have demonstrated their niche on various practical ...problems involving two and three objectives, face significant challenges in many-objective optimization. This paper suggests a unified paradigm, which combines dominance- and decomposition-based approaches, for many-objective optimization. Our major purpose is to exploit the merits of both dominance- and decomposition-based approaches to balance the convergence and diversity of the evolutionary process. The performance of our proposed method is validated and compared with four state-of-the-art algorithms on a number of unconstrained benchmark problems with up to 15 objectives. Empirical results fully demonstrate the superiority of our proposed method on all considered test instances. In addition, we extend this method to solve constrained problems having a large number of objectives. Compared to two other recently proposed constrained optimizers, our proposed method shows highly competitive performance on all the constrained optimization problems.
Substantial efforts have been devoted more recently to presenting various methods for object detection in optical remote sensing images. However, the current survey of datasets and deep learning ...based methods for object detection in optical remote sensing images is not adequate. Moreover, most of the existing datasets have some shortcomings, for example, the numbers of images and object categories are small scale, and the image diversity and variations are insufficient. These limitations greatly affect the development of deep learning based object detection methods. In the paper, we provide a comprehensive review of the recent deep learning based object detection progress in both the computer vision and earth observation communities. Then, we propose a large-scale, publicly available benchmark for object DetectIon in Optical Remote sensing images, which we name as DIOR. The dataset contains 23,463 images and 192,472 instances, covering 20 object classes. The proposed DIOR dataset (1) is large-scale on the object categories, on the object instance number, and on the total image number; (2) has a large range of object size variations, not only in terms of spatial resolutions, but also in the aspect of inter- and intra-class size variability across objects; (3) holds big variations as the images are obtained with different imaging conditions, weathers, seasons, and image quality; and (4) has high inter-class similarity and intra-class diversity. The proposed benchmark can help the researchers to develop and validate their data-driven methods. Finally, we evaluate several state-of-the-art approaches on our DIOR dataset to establish a baseline for future research.
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