Though fluorescence‐tag‐based anti‐counterfeiting technology has distinguished itself with cost‐effective features and huge information loading capacity, the clonable decryption process of ...spatial‐resolved anti‐counterfeiting cannot meet the requirements for high‐security‐level anti‐counterfeiting. Herein, we demonstrate a spatial‐time‐dual‐resolved anti‐counterfeiting system based on new organic–inorganic hybrid halides BAPPZn2(ClyBr1−y)8 (BAPP=1,4‐bis(3‐ammoniopropyl)piperazinium, y=0–1) with ultra‐long room‐temperature phosphorescence (RTP). Remarkably, the afterglow lifetime can be facilely tuned by regulating the halide‐induced heavy‐atom effect and can be identified by the naked eyes or with the help of a simple machine vision system. Therefore, the short‐lived unicolor fluorescence and lasting‐time‐tunable RTP provide the prerequisites for unicolor‐time‐resolved anti‐counterfeiting, which lowers the decryption‐device requirements and further provides the design strategy of advanced portable anti‐counterfeiting technology.
A new zero‐dimensional Zn‐based metal halide with ultra‐long room‐temperature phosphorescence (RTP) is reported. The RTP lifetimes can be facilely regulated via halide engineering, paving the way for designing spatial‐time‐dual‐resolved anti‐counterfeiting materials.
Hydrogen is widely considered to be a sustainable and clean energy alternative to the use of fossil fuels in the future. Its high hydrogen content, nontoxicity, and liquid state at room temperature ...make formic acid a promising hydrogen carrier. Designing highly efficient and low‐cost heterogeneous catalysts is a major challenge for realizing the practical application of formic acid in the fuel‐cell‐based hydrogen economy. Herein, a simple but effective and rapid strategy is proposed, which demonstrates the synthesis of NiPd bimetallic ultrafine particles (UPs) supported on NH2‐functionalized and N‐doped reduced graphene oxide (NH2‐N‐rGO) at room temperature. The introduction of the NH2N group to rGO is the key reason for the formation of the ultrafine and well‐dispersed Ni0.4Pd0.6 UPs (1.8 nm) with relatively large surface area and more active sites. Surprisingly, the as‐prepared low‐cost NiPd/NH2‐N‐rGO dsiplays excellent hydrophilicity, 100% H2 selectivity, 100% conversion, and remarkable catalytic activity (up to 954.3 mol H2 (mol catalyst)−1 h−1) for FA decomposition at room temperature even with no additive, which is much higher than that of the best catalysts so far reported.
Ultrafine NiPd nanoparticles supported on a NH2‐functionalized and N‐doped reduced graphene oxide (NH2‐N‐rGO) substrate are successfully prepared through a facile one‐step strategy. The as‐prepared NiPd/NH2‐N‐rGO catalyst shows prominent catalytic performance (turnover frequency value up to 954.3 h−1), 100% H2 selectivity, and 100% conversion for formic acid dehydrogenation at 298 K without any additive.
Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate ...in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular, the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancies between results simulated by models, as well as those between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large‐scale analyses, (4) results from cloud‐resolving model simulations, and (5) results from large‐scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol‐cloud‐precipitation interactions are suggested.
Key Points
Fundamental theories of the effects of aerosols on cloud microphysical processes
Observations and modeling of aerosol effects on precipitation and weather
Issues and uncertainties in studying aerosol effects on precipitation
Fullerenes have the characteristic of a hollow interior, and this unique feature triggers intuitive inspiration to entrap atoms, ions or clusters inside the carbon cage in the form of endohedral ...fullerenes. In particular, upon entrapping an otherwise unstable metal cluster into a carbon cage, the so-called endohedral clusterfullerenes fulfil the mutual stabilization of the inner metal cluster and the outer fullerene cage with a specific isomeric structure which is often unstable as an empty fullerene. A variety of metal clusters have been reported to form endohedral clusterfullerenes, including metal nitrides, carbides, oxides, sulfides, cyanides and so on, making endohedral clusterfullerenes the most variable and intriguing branch of endohedral fullerenes. In this review article, we present an exhaustive review on all types of endohedral clusterfullerenes reported to date, including their discoveries, syntheses, separations, molecular structures and properties as well as their potential applications in versatile fields such as biomedicine, energy conversion, and so on. At the end, we present an outlook on the prospect of endohedral clusterfullerenes.
Endohedral clusterfullerenes fulfil the mutual stabilization of the inner metal cluster and the outer fullerene cage.
Abstract Context Most cancer patients suffer from both the disease itself and symptoms induced by conventional treatment. Available literature on the clinical effects on cancer patients of ...acupuncture, Tuina, Tai Chi, Qigong, and Traditional Chinese Medicine Five Element Music Therapy (TCM FEMT) reports controversial results. Objectives The primary objective of this meta-analysis was to evaluate the effect of acupuncture, Tuina, Tai Chi, Qigong, and TCM FEMT on various symptoms and quality of life (QOL) in patients with cancer; risk of bias for the selected trials also was assessed. Methods Studies were identified by searching electronic databases (MEDLINE via both PubMed and Ovid, Cochrane Central, China National Knowledge Infrastructure, Chinese Scientific Journal Database, China Biology Medicine, and Wanfang Database). All randomized controlled trials (RCTs) using acupuncture, Tuina, Tai Chi, Qigong, or TCM FEMT published prior to October 2, 2014 were selected, regardless of whether the paper was published in Chinese or English. Results We identified 67 RCTs (5465 patients) that met our inclusion criteria to perform this meta-analysis. Analysis results showed that a significant combined effect was observed for QOL change in patients with terminal cancer in favor of acupuncture and Tuina (Cohen’s d : 0.21-4.55, P <0.05), while Tai Chi and Qigong had no effect on QOL of breast cancer survivors ( P >0.05). The meta-analysis also demonstrated that acupuncture produced small-to-large effects on adverse symptoms including pain, fatigue, sleep disturbance, and some gastrointestinal discomfort; however, no significant effect was found on the frequency of hot flashes (Cohen’s d =-0.02; 95% confidence interval CI -1.49, 1.45; P =0.97; I 2 = 36%) and mood distress ( P >0.05). Tuina relieved gastrointestinal discomfort. TCM FEMT lowered depression level. Tai Chi improved vital capacity of breast cancer patients. High risk of bias was present in 74.63% of the selected RCTs. Major sources of risk of bias were lack of blinding, allocation concealment and incomplete outcome data. Conclusion Taken together, although there are some clear limitations regarding the body of research reviewed in this study, a tentative conclusion can be reached that acupuncture, Tuina, Tai Chi, Qigong, or TCM FEMT represent beneficial adjunctive therapies. Future study reporting in this field should be improved regarding both method and content of interventions and research methods.
Less noble: The Co0.30Au0.35Pd0.35 nanoalloy supported on carbon is reported as a stable, low‐cost, and highly efficient catalyst for the CO‐free hydrogen generation from formic acid dehydrogenation ...at room temperature (see picture). The method may strongly encourage the practical application of formic acid as a hydrogen storage material for fuel cells.
Targeted delivery approaches for cancer therapeutics have shown a steep rise over the past few decades. However, compared to the plethora of successful pre-clinical studies, only 15 passively ...targeted nanocarriers (NCs) have been approved for clinical use and none of the actively targeted NCs have advanced past clinical trials. Herein, we review the principles behind targeted delivery approaches to determine potential reasons for their limited clinical translation and success. We propose criteria and considerations that must be taken into account for the development of novel actively targeted NCs. We also highlight the possible directions for the development of successful tumor targeting strategies.
Speech enhancement model is used to map a noisy speech to a clean speech. In the training stage, an objective function is often adopted to optimize the model parameters. However, in the existing ...literature, there is an inconsistency between the model optimization criterion and the evaluation criterion for the enhanced speech. For example, in measuring speech intelligibility, most of the evaluation metric is based on a short-time objective intelligibility (STOI) measure, while the frame based mean square error (MSE) between estimated and clean speech is widely used in optimizing the model. Due to the inconsistency, there is no guarantee that the trained model can provide optimal performance in applications. In this study, we propose an end-to-end utterance-based speech enhancement framework using fully convolutional neural networks (FCN) to reduce the gap between the model optimization and the evaluation criterion. Because of the utterance-based optimization, temporal correlation information of long speech segments, or even at the entire utterance level, can be considered to directly optimize perception-based objective functions. As an example, we implemented the proposed FCN enhancement framework to optimize the STOI measure. Experimental results show that the STOI of a test speech processed by the proposed approach is better than conventional MSE-optimized speech due to the consistency between the training and the evaluation targets. Moreover, by integrating the STOI into model optimization, the intelligibility of human subjects and automatic speech recognition system on the enhanced speech is also substantially improved compared to those generated based on the minimum MSE criterion.
Data intensive analysis is the major challenge in smart cities because of the ubiquitous deployment of various kinds of sensors. The natural characteristic of geodistribution requires a new computing ...paradigm to offer location-awareness and latency-sensitive monitoring and intelligent control. Fog Computing that extends the computing to the edge of network, fits this need. In this paper, we introduce a hierarchical distributed Fog Computing architecture to support the integration of massive number of infrastructure components and services in future smart cities. To secure future communities, it is necessary to integrate intelligence in our Fog Computing architecture, e.g., to perform data representation and feature extraction, to identify anomalous and hazardous events, and to offer optimal responses and controls. We analyze case studies using a smart pipeline monitoring system based on fiber optic sensors and sequential learning algorithms to detect events threatening pipeline safety. A working prototype was constructed to experimentally evaluate event detection performance of the recognition of 12 distinct events. These experimental results demonstrate the feasibility of the system's city-wide implementation in the future.
PDF
