Motion prediction for the leading vehicle is a critical task for connected autonomous vehicles. It provides a method to model the leading-following vehicle behavior and analysis their interactions. ...In this study, a joint time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The proposed method enables a precise and personalized trajectory prediction for the leading vehicle based on limited inter-vehicle communication signals, such as the vehicle speed and acceleration of the front vehicles. Three different driving styles are first recognized based on an unsupervised clustering algorithm, namely, Gaussian Mixture Model (GMM). The GMM generates a specific driving style for each vehicle based on the speed, acceleration, jerk, time, and space headway features of the leading vehicle. The feature importance of driving style recognition is also evaluated based on the Maximal Information Coefficient (MIC) algorithm. Then, a personalized joint time series modeling (JTSM) method based on the Long Short-Term Memory (LSTM) Recurrent Neural Network model (RNN) is proposed to predict the front vehicle trajectories. The JTSM contains a common LSTM layer and different fully connected regression layers for different driving styles. The proposed method is tested with the Next Generation Simulation (NGSIM) data on the US101, and I-80 highway dataset. The JTSM is tested for making predictions one to five seconds ahead. Results indicate that the proposed personalized JTSM approach shows a significant advantage over the baseline algorithms.
A large number of SARS-related coronaviruses (SARSr-CoV) have been detected in horseshoe bats since 2005 in different areas of China. However, these bat SARSr-CoVs show sequence differences from SARS ...coronavirus (SARS-CoV) in different genes (S, ORF8, ORF3, etc) and are considered unlikely to represent the direct progenitor of SARS-CoV. Herein, we report the findings of our 5-year surveillance of SARSr-CoVs in a cave inhabited by multiple species of horseshoe bats in Yunnan Province, China. The full-length genomes of 11 newly discovered SARSr-CoV strains, together with our previous findings, reveals that the SARSr-CoVs circulating in this single location are highly diverse in the S gene, ORF3 and ORF8. Importantly, strains with high genetic similarity to SARS-CoV in the hypervariable N-terminal domain (NTD) and receptor-binding domain (RBD) of the S1 gene, the ORF3 and ORF8 region, respectively, were all discovered in this cave. In addition, we report the first discovery of bat SARSr-CoVs highly similar to human SARS-CoV in ORF3b and in the split ORF8a and 8b. Moreover, SARSr-CoV strains from this cave were more closely related to SARS-CoV in the non-structural protein genes ORF1a and 1b compared with those detected elsewhere. Recombination analysis shows evidence of frequent recombination events within the S gene and around the ORF8 between these SARSr-CoVs. We hypothesize that the direct progenitor of SARS-CoV may have originated after sequential recombination events between the precursors of these SARSr-CoVs. Cell entry studies demonstrated that three newly identified SARSr-CoVs with different S protein sequences are all able to use human ACE2 as the receptor, further exhibiting the close relationship between strains in this cave and SARS-CoV. This work provides new insights into the origin and evolution of SARS-CoV and highlights the necessity of preparedness for future emergence of SARS-like diseases.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This paper establishes a posterior convergence rate theorem for general Markov chains. Our approach is based on the Hausdorff α-entropy introduced by Xing (Electronic Journal of Statistics 2:848-62, ...2008) and Xing and Ranneby (Journal of Statistical Planning and Inference 139 (7):2479-89, 2009). As an application we illustrate our results on a non linear autoregressive model.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
We disclose that the carbonates of 4‐hydroxy‐2‐cyclopentenones can form π‐allylpalladium‐based 1,2‐carbodipoles, which isomerize to interesting η2‐Pd0‐cyclopentadienone complexes. Compared with the ...labile parent cyclopentadienone, the HOMO energy of the related η2‐complex was significantly raised via the back‐bonding of Pd0 as a π‐Lewis base, rendering the uncoordinated C=C bond an electron‐richer dienophile in inverse‐electron‐demand aza‐Diels–Alder‐type reactions with diverse 1‐azadienes. The vinylogous (aza)Morita–Baylis–Hillman or cross Rauhut–Currier addition to (imine)carbonyls or activated alkenes, respectively, was also realized to afford chiral 4+2 or 2+2 cycloadducts, respectively, after trapping the re‐generated π‐allylpalladium species. New C1‐symmetric ligands from simple chiral sources were developed, exhibiting high stereoselectivity even with racemic substrates via an unusual dynamic kinetic resolution process. Besides, tropone could be similarly activated by a Pd0 complex.
π‐Allylpalladium‐based 1,2‐carbodipoles were generated from the carbonate derivatives of 4‐hydroxy‐2‐cyclopentenones and isomerized in situ to electronically neutral η2‐Pd0‐cyclopentadienone complexes. These HOMO‐raised cyclopentadienones participate, via π‐Lewis base activation, in inverse‐electron‐demand Diels–Alder‐type cycloadditions and cascade Morita–Baylis–Hillman‐ or Rauhut–Currier‐type addition/allylic substitution reactions with diverse electrophiles.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Dynamic state estimation is of considerable importance to the system monitoring, advanced control, and energy management of electrified vehicles (EVs). Among the dynamic states of various vehicle ...systems, the brake pressure is a key state that reflects the braking intent and maneuver of a driver and is highly correlated with the safety and energy performance of an EV. Thus, it is worth formulating a high-precision estimation algorithm for the brake pressure to better identify the braking intent of a driver and further enhance the multiperformance of the EVs. In this article, an integrated time-series model (TSM) based on multivariate deep recurrent neural networks (RNN) with long short-term memory (LSTM) units is developed for the dynamic estimation of the brake pressure of EVs. The naturalistic driving data are collected using a real electric vehicle under standard driving cycle scenarios. The signals of the vehicle and system states are measured using the controller area network (CAN) bus and preprocessed for model training and prediction. Next, a real-time multivariate LSTM-RNN model for brake pressure estimation is constructed based on the integrated speed estimation model. The real-time scheme iteratively estimates the future velocity and integrates this signal with other vehicle states to estimate a precise value of the braking pressure. The proposed integrated TSM approach is compared with several existing baseline methods to demonstrate the advantage of the method. The testing results indicate that the proposed integrated TSM method can achieve a more reliable multistep prediction with a higher accuracy compared to that of the other methods, which demonstrates the feasibility and effectiveness of the proposed approach.
Polycyclic polyprenylated acylphloroglucinols (PPAPs) are a class of hybrid natural products sharing the mevalonate/methylerythritol phosphate and polyketide biosynthetic pathways and showing ...considerable structure and bioactivity diversity. This review discusses the progress of research into the chemistry and biological activity of 421 natural PPAPs in the past 11 years as well as in-depth studies of biological activities and total synthesis of some PPAPs isolated before 2006. We created an online database of all PPAPs known to date at http://www.chem.uky.edu/research/grossman/PPAPs. Two subclasses of biosynthetically related metabolites, spirocyclic PPAPs with octahydrospirocyclohexan-1,5′-indene-2,4,6-trione core and complicated PPAPs produced by intramolecular 4 + 2 cycloadditions of MPAPs, are brought into the PPAP family. Some PPAPs’ relative or absolute configurations are reassigned or critically discussed, and the confusing trivial names in PPAPs investigations are clarified. Pharmacologic studies have revealed a new molecular mechanism whereby hyperforin and its derivatives regulate neurotransmitter levels by activating TRPC6 as well as the antitumor mechanism of garcinol and its analogues. The antineoplastic potential of some type B PPAPs such as oblongifolin C and guttiferone K has increased significantly. As a result of the recent appearances of innovative synthetic methods and strategies, the total syntheses of 22 natural PPAPs including hyperforin, garcinol, and plukenetione A have been accomplished.
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IJS, KILJ, NUK, PNG, UL, UM
Organic–inorganic hybrid perovskite solar cells (PSCs) are currently attracting significant interest owing to their promising outdoor performance. However, the ability of indoor light harvesting of ...the perovskites and corresponding device performance are rarely reported. Here, the potential of planar PSCs in harvesting indoor light for low‐power consumption devices is investigated. Ionic liquid of 1‐butyl‐3‐methylimidazolium tetrafluoroborate (BMIMBF4) is employed as a modification layer of 6,6‐phenyl‐C61‐butyric acid methyl ester) (PCBM) in the inverted PSCs. The incorporation of BMIMBF4 not only paves the interface contact between PCBM and electrode, but also facilitates the electron transport and extraction owing to the efficient passivation of the surface trap states. Moreover, BMIMBF4 with excellent thermal stability can act as a protective layer by preventing the erosion of moisture and oxygen into the perovskite layer. The resulting devices present a record indoor power conversion efficiency (PCE) of 35.20% under fluorescent lamps of 1000 lux, and an impressive PCE of 19.30% under 1 sun illumination. The finding in this work verifies the excellent indoor performance of PSCs to meet the requirements of eco‐friendly economy.
Ionic liquid of 1‐butyl‐3‐methylimidazolium tetrafluoroborate (BMIMBF4) is employed as a cathode modification and a protective layer to fabricate indoor perovskite solar cells. The resulting devices deliver an impressive power conversion efficiency (PCE) of 19.30% at 1 sun illumination, and a record indoor PCE of 35.20% under fluorescent lamp with 1000 lux, which is the highest value reported so far for indoor solar cells.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
We investigate a new mechanism to create large curvature perturbations on small scales due to parameter resonance in a single-field inflationary model with a small periodic structure upon the ...potential. After reentering the horizon, the amplified curvature perturbations can lead to observable primordial black holes as well as stochastic gravitational waves. The mass of primordial black holes and frequency of the induced gravitational waves depend on the model parameters. The resulted primordial black hole could constitute all dark matter or a fraction of dark matter in the universe, and corresponding stochastic gravitational waves fall in the frequency band measurable for the pulsar timing array and the space-based gravitational wave detectors.
Cerambycidae (longhorn beetles) and related families in the superfamily Chrysomeloidea are important components of forest ecosystems and play a key role in nutrient cycling and pollination. Using ...full mitochondrial genomes and dense taxon sampling, the phylogeny of Chrysomeloidea with a focus on Cerambycidae and allied families was explored. We used 151 mitochondrial genomes (75 newly sequenced) covering all families and 29 subfamilies of Chrysomeloidea. Our results reveal that (i) Chrysomelidae (leaf beetles) are sister to all other chrysomeloid families; (ii) Cerambycidae sensu stricto (s. s.) is polyphyletic due to the inclusion of other families that split Cerambycidae into a ‘lamiine’ clade comprising Lepturinae sensu lato (s. l.) + (Lamiinae + Spondylidinae) and a ‘cerambycine’ clade comprising Dorcasominae + (Cerambycinae + Prioninae s. l.); (iii) the subfamilies within the two clades of Cerambycidae s. s. were monophyletic, except for the placement of Necydalinae nested in Lepturinae, and the placement of Parandrinae within Prioninae (now considered as tribes Necydalini and Parandrini, respectively); (iv) smaller families were grouped into two major clades: one composed of Disteniidae+Vesperidae and the other composed of Orsodacnidae + (Megalopodidae + Oxypeltidae); (v) relationships among the four major clades were poorly supported but were resolved as ((cerambycines + (Disteniidae + Vesperidae) + Orsodacnidae + (Megalopodidae + Oxypeltidae)) + lamiines. Divergence time analyses estimated that Chrysomeloidea originated ca. 154.1 Mya during the late Jurassic, and most subfamilies of Cerambycidae originated much earlier than subfamilies of Chrysomelidae. The diversification of families within Chrysomeloidea was largely coincident with the radiation of angiosperms during the Early Cretaceous.
Seventy‐five full mitochondrial genomes were newly generated and combined with existing Genbank data, for a dataset of 151 mitochondrial genomes covering all families and 29 subfamilies of Chrysomeloidea.
The mitogenomes provide a framework for the phylogeny and classification of Chrysomeloidea, which confirm and extend existing notions of deep‐level relationships of Cerambycidae and the smaller families of Chrysomeloidea.
Divergence time analyses estimated that Chrysomeloidea originated ca. 154.1 Mya in the late Jurassic.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Driver decisions and behaviors are essential factors that can affect the driving safety. To understand the driver behaviors, a driver activities recognition system is designed based on the deep ...convolutional neural networks (CNN) in this paper. Specifically, seven common driving activities are identified, which are the normal driving, right mirror checking, rear mirror checking, left mirror checking, using in-vehicle radio device, texting, and answering the mobile phone, respectively. Among these activities, the first four are regarded as normal driving tasks, while the rest three are classified into the distraction group. The experimental images are collected using a low-cost camera, and ten drivers are involved in the naturalistic data collection. The raw images are segmented using the Gaussian mixture model to extract the driver body from the background before training the behavior recognition CNN model. To reduce the training cost, transfer learning method is applied to fine tune the pre-trained CNN models. Three different pre-trained CNN models, namely, AlexNet, GoogLeNet, and ResNet50 are adopted and evaluated. The detection results for the seven tasks achieved an average of 81.6% accuracy using the AlexNet, 78.6% and 74.9% accuracy using the GoogLeNet and ResNet50, respectively. Then, the CNN models are trained for the binary classification task and identify whether the driver is being distracted or not. The binary detection rate achieved 91.4% accuracy, which shows the advantages of using the proposed deep learning approach. Finally, the real-world application are analyzed and discussed.
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