Abstract
In this work, we adopt a cosmological model-independent approach for the first time to test the question of whether the mass density power-law index (
γ
) of strong gravitational lensing ...systems (SGLSs) evolves with redshift, and the joint light-curve Type Ia supernova (SNe Ia) sample and the quasar sample from Risaliti & Lusso are used to provide the luminosity distances to be calibrated. Our work is based on the flat universe assumption and the cosmic distance duality relation. A reliable data-matching method is used to pair SGLS–SNe and SGLS–quasars. By using the maximum likelihood method to constrain the luminosity distance and
γ
index, we obtain the likelihood function values for the evolved and nonevolved cases, and then use the Akaike weights and the Bayesian Information Criterion (BIC) selection weights to compare the advantages and disadvantages of these two cases. We find that the
γ
index is slightly more likely to be a nonevolutionary model for
γ
= 2 in the case of the currently used samples with low redshift (
z
l
< ∼ 0.66). With Akaike weights, the relative probabilities are 66.3% versus 33.7% and 69.9% versus 30.1% for the SGLS + SNe Ia sample and SGLS + quasar sample, respectively, and with the BIC selection weights, the relative probabilities are 87.4% versus 12.6% and 52.0% versus 48.0% for the two samples. In the evolving case for the relatively low-redshift lenses (SGLS + SNe Ia), with redshift 0.0625–0.659,
γ
=
2.058
−
0.040
+
0.041
–
0.136
−
0.165
+
0.163
z
. At high redshift (SGLS + quasar), with redshift 0.0625–1.004,
γ
=
2.051
−
0.077
+
0.076
–
0.171
−
0.196
+
0.214
z
. Although not the more likely model, this evolved
γ
case also fits the data well, with a negative and mild evolution for both low- and high-redshift samples.
Pyrene‐based π‐conjugated materials are considered to be an ideal organic electro‐luminescence material for application in semiconductor devices, such as organic light‐emitting diodes (OLEDs), ...organic field‐effect transistors (OFETs) and organic photovoltaics (OPVs), and so forth. However, the great drawback of employing pyrene as an organic luminescence material is the formation of excimer emission, which quenches the efficiency at high concentration or in the solid‐state. Thus, in order to obtain highly efficient optical devices, scientists have devoted much effort to tuning the structure of pyrene derivatives in order to realize exploitable properties by employing two strategies, 1) introducing a variety of moieties at the pyrene core, and 2) exploring effective and convenient synthetic strategies to functionalize the pyrene core. Over the past decades, our group has mainly focused on synthetic methodologies for functionalization of the pyrene core; we have found that formylation/acetylation or bromination of pyrene can selectly lead to functionalization at K‐region by Lewis acid catalysis. Herein, this Minireview highlights the direct synthetic approaches (such as formylation, bromination, oxidation, and de‐tert‐butylation reactions, etc.) to functionalize the pyrene in order to advance research on luminescent materials for organic electronic applications. Further, this article demonstrates that the future direction of pyrene chemistry is asymmetric functionalization of pyrene for organic semiconductor applications and highlights some of the classical asymmetric pyrenes, as well as the latest breakthroughs. In addition, the photophysical properties of pyrene‐based molecules are briefly reviewed. To give a current overview of the development of pyrene chemistry, the review selectively covers some of the latest reports and concepts from the period covering late 2011 to the present day.
Pepping up pyrene: This Minireview highlights direct synthetic approaches to functionalize the pyrene at the active sites (the 1‐, 3‐, 6‐, and 8‐positions), the K‐region (the 4‐, 5‐, 9‐, and 10‐positions), and the nodal plane (the 2‐ and 7‐positions), in order to advance research on luminescent materials for organic electronic applications. Further, this article demonstrates the future direction of pyrene chemistry for organic semiconductor application and highlights some classical asymmetric pyrenes, as well as the latest breakthroughs.
This article is written to provide an up-to-date review of porphyrin-based materials used in organic solar cells (OSCs). During the past two decades, OSCs have been the subject of extensive research ...and significant efforts have been devoted to developing low-cost OSCs, and they are not far from commercialization. Porphyrin and its analogues have been successfully applied to different optoelectronic devices, especially attaining remarkable fame when applied in dye sensitized solar cells. Despite the initial failures of their application in OSCs, porphyrins still attract much attention because of their structural versatility and recently realized significant improvement. In this review, we focus on summarizing the recent progress in porphyrin-based photovoltaic materials, including polymers, dyads, triads, small-molecules, and so on. We hope this paper could provide an in-depth study on the structure-property-performance relationship and provide a guideline for the further development of porphyrin-based and even other photovoltaic materials.
This article is written to provide an up-to-date review of porphyrin-based materials used in organic solar cells (OSCs).
In this paper, we focus on heterogeneous features learning for RGB-D activity recognition. We find that features from different channels (RGB, depth) could share some similar hidden structures, and ...then propose a joint learning model to simultaneously explore the shared and feature-specific components as an instance of heterogeneous multi-task learning. The proposed model formed in a unified framework is capable of: 1) jointly mining a set of subspaces with the same dimensionality to exploit latent shared features across different feature channels, 2) meanwhile, quantifying the shared and feature-specific components of features in the subspaces, and 3) transferring feature-specific intermediate transforms (i-transforms) for learning fusion of heterogeneous features across datasets. To efficiently train the joint model, a three-step iterative optimization algorithm is proposed, followed by a simple inference model. Extensive experimental results on four activity datasets have demonstrated the efficacy of the proposed method. Anew RGB-D activity dataset focusing on human-object interaction is further contributed, which presents more challenges for RGB-D activity benchmarking.
Deep‐blue fluorescent compounds are particularly important in organic light‐emitting devices (OLEDs). A donor–accepotor (DA)‐type blue‐emitting compound, ...1‐(10‐(4‐methoxyphenyl)anthracen‐9‐yl)‐4‐(10‐(4‐cyanophenyl)anthracen‐9‐yl)benzene (BD3), is synthesized, and for comparison, a nonDA‐type compound, 1,4‐bis(10‐phenylanthracene‐9‐yl)benzene (BD1) and a weak DA‐type compound, 1‐(10‐phenylanthracen‐9‐yl)‐4‐(10‐(4‐cyanophenyl)anthracen‐9‐yl)‐benzene (BD2), are also synthesized. The twisted conformations of the two anthracene units in the compounds, confirmed by single crystal X‐ray analysis, effectively prevent π‐conjugation, and the compound shows deep‐blue photoluminescence (PL) with a high PL quantum efficiency, almost independent of the solvent polarity, resulting from the absence of an intramolecular charge transfer state. The DA‐type molecule BD3 in a non‐doped device exhibits a maximum external quantum efficiency (EQE) of 4.2% with a slight roll‐off, indicating good charge balance due to the DA‐type molecular design. In the doped device with 4,4′‐bis(N‐carbazolyl)‐1,1′‐biphenyl (CBP) host, the BD3 exhibits higher EQE than 10% with Commission International de L'Eclairge (CIE) coordinates of (0.15, 0.06) and a narrow full‐width at half‐maximum of 45 nm, which is close to the CIE of the high definition television standard blue.
Donor–accepotor (DA)‐type deep‐blue fluorescent compounds are synthesized. Twisted conformations of the two anthracene units in the compounds effectively prevent π‐conjugation. The compounds show deep‐blue photoluminescence (PL) with a high quantum efficiency, almost independent of solvent polarity. The weak DA‐type compound exhibits an external quantum efficiency >10% and deep‐blue emission with CIE (0.15, 0.06) in a light‐emitting device.
Early Action Prediction by Soft Regression Hu, Jian-Fang; Zheng, Wei-Shi; Ma, Lianyang ...
IEEE transactions on pattern analysis and machine intelligence,
11/2019, Letnik:
41, Številka:
11
Journal Article
Recenzirano
Odprti dostop
We propose a novel approach for predicting on-going action with the assistance of a low-cost depth camera. Our approach introduces a soft regression-based early prediction framework. In this ...framework, we estimate soft labels for the subsequences at different progress levels, jointly learned with an action predictor. Our formulation of soft regression framework 1) overcomes a usual assumption in existing early action prediction systems that the progress level of on-going sequence is given in the testing stage; and 2) presents a theoretical framework to better resolve the ambiguity and uncertainty of subsequences at early performing stage. The proposed soft regression framework is further enhanced in order to take the relationships among subsequences and the discrepancy of soft labels over different classes into consideration, so that a Multiple Soft labels Recurrent Neural Network (MSRNN) is finally developed. For real-time performance, we also introduce a new RGB-D feature called "local accumulative frame feature (LAFF)", which can be computed efficiently by constructing an integral feature map. Our experiments on three RGB-D benchmark datasets and an unconstrained RGB action set demonstrate that the proposed regression-based early action prediction model outperforms existing models significantly and also show that the early action prediction on RGB-D sequence is more accurate than that on RGB channel.
We investigate the correlation between the supermassive black holes (SMBHs) mass (Mbh) and the stellar velocity dispersion (σ*) in two types of host galaxies: the early-type bulges (disc galaxies ...with classical bulges or elliptical galaxies) and pseudo-bulges. In the form log (Mbh/M⊙) =α+β log (σ*/200 km s−1), the best-fitting results for the 39 early-type bulges are the slope β= 4.06 ± 0.28 and the normalization α= 8.28 ± 0.05; the best-fitting results for the nine pseudo-bulges are β= 4.5 ± 1.3 and α= 7.50 ± 0.18. Both relations have intrinsic scatter in log Mbh of ≲0.27 dex. The Mbh–σ* relation for pseudo-bulges is different from the relation in the early-type bulges over the 3σ significance level. The contrasting relations indicate the formation and growth histories of SMBHs depend on their host type. The discrepancy between the slope of the Mbh–σ* relations using different definition of velocity dispersion vanishes in our sample, a uniform slope will constrain the coevolution theories of the SMBHs and their host galaxies more effectively. We also find the slope for the ‘core’ elliptical galaxies at the high-mass range of the relation appears steeper (β≃ 5–6), which may be the imprint of their origin of dissipationless mergers.
Despite rapid advances in modern medical technology and significant improvements in survival rates of many cancers, pancreatic cancer is still a highly lethal gastrointestinal cancer with a low ...5-year survival rate and difficulty in early detection. At present, the incidence and mortality of pancreatic cancer are increasing year by year worldwide, no matter in the United States, Europe, Japan, or China. Globally, the incidence of pancreatic cancer is projected to increase to 18.6 per 100000 in 2050, with the average annual growth of 1.1%, meaning that pancreatic cancer will pose a significant public health burden. Due to the special anatomical location of the pancreas, the development of pancreatic cancer is usually diagnosed at a late stage with obvious clinical symptoms. Therefore, a comprehensive understanding of the risk factors for pancreatic cancer is of great clinical significance for effective prevention of pancreatic cancer. In this paper, the epidemiological characteristics, developmental trends, and risk factors of pancreatic cancer are reviewed and analyzed in detail.
In situ and ex situ NMR for battery research Hu, Jian Zhi; Jaegers, Nicholas R; Hu, Mary Y ...
Journal of physics. Condensed matter,
11/2018, Letnik:
30, Številka:
46
Journal Article
Recenzirano
A rechargeable battery stores readily convertible chemical energy to operate a variety of devices such as mobile phones, laptop computers, electric automobiles, etc. A battery generally consists of ...four components: a cathode, an anode, a separator and electrolytes. The properties of these components jointly determine the safety, the lifetime, and the electrochemical performance. They also include, but are not limited to, the power density and the charge as well as the recharge time/rate associated with a battery system. An extensive amount of research is dedicated to understanding the physical and chemical properties associated with each of the four components aimed at developing new generations of battery systems with greatly enhanced safety and electrochemical performance at a significantly reduced cost for large scale applications. Advanced characterization tools are a prerequisite to fundamentally understanding battery materials. Considering that some of the key electrochemical processes can only exist under in situ conditions, which can only be captured under working battery conditions when electric wires are attached and current and voltage are applied, make in situ detection critical. Nuclear magnetic resonance (NMR), a non-invasive and atomic specific tool, is capable of detecting all phases, including crystalline, amorphous, liquid and gaseous phases simultaneously and is ideal for in situ detection on a working battery system. Ex situ NMR on the other hand can provide more detailed molecular or structural information on stable species with better spectral resolution and sensitivity. The combination of in situ and ex situ NMR, thus, offers a powerful tool for investigating the detailed electrochemistry in batteries.
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