Air Pollution Forecasts: An Overview Bai, Lu; Wang, Jianzhou; Ma, Xuejiao ...
International journal of environmental research and public health,
04/2018, Letnik:
15, Številka:
4
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Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain ...concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.
This paper proposes a non-stationary three-dimensional (3D) irregular-shaped geometry-based stochastic model (IS-GBSM) for fifth generation (5G) and beyond massive multiple-input multiple-output ...(MIMO) millimeter wave (mmWave) unmanned aerial vehicle (UAV) channels. This is the first sixth generation (6G) massive MIMO mmWave UAV IS-GBSM that can model the UAV channel space-time non-stationarity, and can describe the impact of some unique UAV-related parameters, e.g., the UAV's moving direction, height, and speed, on channel statistical properties. To better represent the space-time non-stationarity in UAV scenarios, a novel UAV-related space-time cluster evolution algorithm is developed. The developed algorithm considers the characteristics of UAV communications on the modeling of space-time non-stationarity. Based on the proposed model, some channel statistical properties are derived and thoroughly investigated, including the space-time-frequency correlation function, Doppler power spectral density, envelope level crossing rate, and average fade duration. Some numerical results and interesting observations are given, and the impact of UAV-related parameters on channel statistical properties is explored, which can provide assistance for the design of 6G massive MIMO mmWave UAV communication systems. Finally, the applicability of the proposed model is verified by the close agreement between simulation results and measurement.
Transcription Under Torsion Ma, Jie; Bai, Lu; Wang, Michelle D.
Science,
06/2013, Letnik:
340, Številka:
6140
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In cells, RNA polymerase (RNAP) must transcribe supercoiled DNA, whose torsional state is constantly changing, but how RNAP deals with DNA supercoiling remains elusive. We report direct measurements ...of individual Escherichia coli RNAPs as they transcribed supercoiled DNA. We found that a resisting torque slowed RNAP and increased its pause frequency and duration. RNAP was able to generate 11 ± 4 piconewton-nanometers (mean ± standard deviation) of torque before stalling, an amount sufficient to melt DNA of arbitrary sequence and establish RNAP as a more potent torsional motor than previously known. A stalled RNAP was able to resume transcription upon torque relaxation, and transcribing RNAP was resilient to transient torque fluctuations. These results provide a quantitative framework for understanding how dynamic modification of DNA supercoiling regulates transcription.
Nucleosome positioning in the genome is essential for the regulation of many nuclear processes. We currently have limited capability to predict nucleosome positioning in vivo, especially the ...locations and sizes of nucleosome depleted regions (NDRs). Here, we present a thermodynamic model that incorporates the intrinsic affinity of histones, competitive binding of sequence-specific factors, and nucleosome remodeling to predict nucleosome positioning in budding yeast. The model shows that the intrinsic affinity of histones, at near-saturating histone concentration, is not sufficient in generating NDRs in the genome. However, the binding of a few factors, especially RSC towards GC-rich and poly(A/T) sequences, allows us to predict ~ 66% of genome-wide NDRs. The model also shows that nucleosome remodeling activity is required to predict the correct NDR sizes. The validity of the model was further supported by the agreement between the predicted and the measured nucleosome positioning upon factor deletion or on exogenous sequences introduced into yeast. Overall, our model quantitatively evaluated the impact of different genetic components on NDR formation and illustrated the vital roles of sequence-specific factors and nucleosome remodeling in this process.
In this brief, a distributed control algorithm is proposed to solve the economic dispatch problem. Without a central control unit, the generators work collaboratively to minimize the generation cost ...while balancing the supply and demand. The proposed method is based on consensus protocols and the saddle point dynamics. The consensus protocols are employed to estimate the global information in a distributed fashion, and the saddle point dynamics are leveraged to search for the optimal solution of the economic dispatch problem. By utilizing Lyapunov stability analysis, exponential stability of the optimal solution is derived if the capacity limits of the generators are not considered; with the capacity limits, practical stability of the optimal solution is obtained. No global information is needed in the proposed method, and the requirement on initial conditions of the state variables is mild. Several case studies on the IEEE 9-bus and IEEE 118-bus systems are presented to demonstrate the effectiveness of the proposed algorithms.
With the rapid development of information technology and system norms and the incongruity of personnel training speed, the development of news media reports has caused a large number of negative ...effects. From the current situation of the development of news media reports, due to the lack of perfect management, the difference in media literacy between users and enterprises, entertainment to death, rampant consumer culture, and many other factors, the network media reports are chaotic. In the proposed model Fuzzy Fredholm Integral Market Efficiency (FFI-ME) for the media coverage. With the FFI-ME model, the information technology computes the news media data for the estimation of the coverage to achieve market efficiency. The FFI-ME model uses the Fredholm Integral model to compute the market efficiency for the media data in China. The FFI-ME model computes the news data in China and clusters the data for the classification and detection of the instances in the equation. Through the Integral Fredholm model, the features of the news are estimated to compute the media coverage and efficiency of the news media data. The model uses the Deep learning model for the classification of the data instance in the media data. The simulation analysis expressed that the proposed FFI-ME model achieves a higher classification data accuracy of the 98%.
As the fifth-generation (5G) wireless communication networks are at the stage of commercial deployment, beyond 5G (B5G)/sixth-generation (6G) wireless communication networks have also been under ...extensive research. In the B5G/6G era, the vision of the wireless communication network is the so-termed space-air-ground-sea integrated network (SAGSIN), which will focus on more various and dynamic communication scenarios, including vehicle-to-vehicle (V2V), high-speed train (HST), unmanned aerial vehicle (UAV), satellite, and maritime communications. Meanwhile, B5G/6G communication systems will also employ two potential technologies, i.e., millimeter wave (mmWave)-terahertz (THz) and ultra-massive multiple-input multiple-output (MIMO), and have a new development trend, i.e., integrated sensing and communication (ISAC) systems. For the successful design of B5G/6G communication systems, accurate and easy-to-use channel models, which can fully mimic the underlying characteristics and features of B5G/6G channels, are indispensable. However, more diverse communication scenarios, higher frequency band, larger-scale antenna array, and the emergence of ISAC systems in B5G/6G will bring two significant points of concern for wireless channels, i.e., channel non-stationarity and channel consistency. Channel non-stationarity is a typical channel characteristic, whereas channel consistency is an inherent channel physical feature. To capture those, extensive works have been carried out, but have not yet been adequately summarized, compared, and analyzed. This paper first provides the definitions of channel non-stationarity and channel consistency from mathematical and physical perspectives, and then discusses the necessity of capturing them for various wireless applications. Recent advances in the topic of capturing channel non-stationarity and channel consistency are further elaborated and investigated. Additionally, simulation results concerning them are provided and analyzed. Finally, promising and meaningful future research directions for this topic are outlined.
This paper is focused on the observer-based adaptive fuzzy control problem for nonlinear stochastic systems with the nonstrict-feedback form, in which some complicated and challenging issues ...including unmeasurable states, input quantization and actuator faults are addressed. The fuzzy logic systems are introduced to approximate the nonlinear functions existing in the control system. A fuzzy observer is designed to observe the unavailable state variables. In order to handle the negative effects resulting from input quantization and actuator faults, a damping term with the estimation of unknown bounds as well as a positive time-varying integral function are constructed, respectively. Furthermore, an observer-based adaptive fuzzy control scheme is proposed for the considered systems to compensate for the effects of input quantization and actuator fault based on adaptive backstepping approach. The proposed control strategy can guarantee that all the signals in the closed-loop system are bounded. Finally, simulation results are provided to illustrate the effectiveness of the proposed adaptive control scheme.
Reported is a highly chemoselective intermolecular annulation of indole‐based biaryls with bromoalkyl alkynes by using palladium/norbornene (Pd/NBE) cooperative catalysis. This reaction is realized ...through a sequence of Catellani‐type C−H alkylation, alkyne insertion, and indole dearomatization, by forming two C(sp2)−C(sp3) and one C(sp2)−C(sp2) bonds in a single chemical operation, thus providing a diverse range of pentacyclic molecules, containing a spiroindolenine fragment, in good yields with excellent functional‐group tolerance. Preliminary mechanistic studies reveal that C−H bond cleavage is likely involved in the rate‐determining step, and the indole dearomatization might take place through an olefin coordination/insertion and β‐hydride elimination Heck‐type pathway.
A sequence of three: A novel palladium/norbornene (NBE) catalyzed intermolecular annulation of indole‐derived aryl iodides with tethered bromoalkyl alkynes has been developed for the rapid construction of pentacyclic scaffolds containing a spiroindolenine fragment. This reaction was realized through a C−H alkylation, alkyne insertion, and indole dearomatization sequence.
Brain-derived neurotrophic factor (BDNF) and serotonin (5-hydroxytryptamine, 5-HT) are two seemingly distinct signaling systems that play regulatory roles in many neuronal functions including ...survival, neurogenesis, and synaptic plasticity. A common feature of the two systems is their ability to regulate the development and plasticity of neural circuits involved in mood disorders such as depression and anxiety. BDNF promotes the survival and differentiation of 5-HT neurons. Conversely, administration of antidepressant selective serotonin reuptake inhibitors (SSRIs) enhances BDNF gene expression. There is also evidence for synergism between the two systems in affective behaviors and genetic epitasis between BDNF and the serotonin transporter genes.
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